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MICCAI 2021 - Accepted Papers and Reviews
List of topics: Clinical applications - Abdomen Clinical applications - Breast Clinical applications - Cardiac Clinical applications - Dermatology Clinical applications - Fetal Imaging Clinical applications - Lung Clinical applications - Musculoskeletal Clinical applications - Neuroimaging - Brain Development Clinical applications - Neuroimaging - DWI and Tractography Clinical applications - Neuroimaging - Functional Brain Networks Clinical applications - Neuroimaging - Others Clinical applications - Oncology Clinical applications - Ophthalmology Clinical applications - Vascular Computational (Integrative) Pathology Computational Anatomy and Physiology Computer Aided Diagnosis Image Reconstruction Image Registration Image Segmentation Image-Guided Interventions and Surgery Integration of Imaging with Non-Imaging Biomarkers Interventional Imaging Systems Interventional Simulation Systems Machine Learning - Active Learning Machine Learning - Attention models Machine Learning - Domain adaptation Machine Learning - Interpretability / Explainability Machine Learning - Reinforcement learning Machine Learning - Self-supervised learning Machine Learning - Semi-supervised learning Machine Learning - Uncertainty Machine Learning - Weakly supervised learning Medical Robotics and Haptics Modalities - Biophotonics Modalities - CT Modalities - EEG/ECG Modalities - Histopathology Modalities - MRI Modalities - Microscopy Modalities - PET/SPECT Modalities - Text (clinical/radiology reports) Modalities - Ultrasound Modalities - Video Modalities - other Outcome/disease prediction Population Imaging and Imaging Genetics Surgical Data Science Surgical Planning and Simulation Surgical Skill and Work Flow Analysis Surgical Visualization and Mixed, Augmented and Virtual Reality Visualisation in Biomedical Imaging Back to top

List of papers by topics


Clinical applications - Abdomen

  • AMINN: Autoencoder-based Multiple Instance Neural Network Improves Outcome Prediction of Multifocal Liver Metastases
  • Balanced-MixUp for highly imbalanced medical image classification
  • Colorectal Polyp Classification from White-light Colonoscopy Images via Domain Alignment
  • Comprehensive Importance-based Selective Regularization for Continual Segmentation Across Multiple Sites
  • Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images
  • Deep-Cleansing: Deep-learning based Electronic Cleansing in Dual-energy CT Colonography
  • Early Detection of Liver Fibrosis Using Graph Convolutional Networks
  • Effective Pancreatic Cancer Screening on Non-contrast CT Scans via Anatomy-Aware Transformers
  • Hybrid graph convolutional neural networks for anatomical segmentation
  • Identifying Quantitative and Explanatory Tumor Indexes from Dynamic Contrast Enhanced Ultrasound
  • Learning from Subjective Ratings Using Auto-Decoded Deep Latent Embeddings
  • Learning More for Free - A Multi Task Learning Approach for Improved Pathology Classification in Capsule Endoscopy
  • Learning-based attenuation quantification in abdominal ultrasound
  • Modality-aware Mutual Learning for Multi-modal Medical Image Segmentation
  • Motion Correction for Liver DCE-MRI with Time-Intensity Curve Constraint
  • Noisy Labels are Treasure: Mean-Teacher-Assisted Confident Learning for Hepatic Vessel Segmentation
  • Non-invasive Assessment of Hepatic Venous Pressure Gradient (HVPG) Based on MR Flow Imaging and Computational Fluid Dynamics
  • Pancreas CT Segmentation by Predictive Phenotyping
  • Personalized CT Organ Dose Estimation from Scout Images
  • Personalized Respiratory Motion Model Using Conditional Generative Networks for MR-Guided Radiotherapy
  • Predicting Symptoms from Multiphasic MRI via Multi-Instance Attention Learning for Hepatocellular Carcinoma Grading
  • Reciprocal Learning for Semi-supervised Segmentation
  • Revisiting iterative highly efficient optimisation schemes in medical image registration
  • Selective Learning from External Data for CT Image Segmentation
  • Semi-Supervised Unpaired Multi-Modal Learning for Label-Efficient Medical Image Segmentation
  • Sequential Learning on Liver Tumor Boundary Semantics and Prognostic Biomarker Mining
  • Shallow Attention Network for Polyp Segmentation
  • Surgical Workflow Anticipation using Instrument Interaction
  • TumorCP: A Simple but Effective Object-Level Data Augmentation for Tumor Segmentation
  • Unsupervised Contrastive Learning of Radiomics and Deep Features for Label-Efficient Tumor Classification
  • Unsupervised Domain Adaptation for Small Bowel Segmentation using Disentangled Representation
  • Using Multiple Images and Contours for Deformable 3D-2D Registration of a Preoperative CT in Laparoscopic Liver Surgery

    • Clinical applications - Breast

  • A Neural Framework for Multi-Variable Lesion Quantification Through B-mode Style Transfer
  • Beyond Non-Maximum Suppression - Detecting Lesions in Digital Breast Tomosynthesis Volumes
  • BI-RADS Classification of Calcification on Mammograms
  • DAE-GCN: Identifying Disease-Related Features for Disease Prediction
  • Domain Generalization for Mammography Detection via Multi-style and Multi-view Contrastive Learning
  • Enhanced Breast Lesion Classification via Knowledge Guided Cross-Modal and Semantic Data Augmentation
  • Graph Transformers for Characterization and Interpretation of Surgical Margins
  • Interactive smoothing parameter optimization in DBT Reconstruction using Deep learning
  • Learned super resolution ultrasound for improved breast lesion characterization
  • Multi-view analysis of unregistered medical images using cross-view transformers
  • Radiomics-informed Deep Curriculum Learning for Breast Cancer Diagnosis
  • Residual Feedback Network for Breast Lesion Segmentation in Ultrasound Image
  • Retina-Match: Ipsilateral Mammography Lesion Matching in a Single Shot Detection Pipeline
  • Self-adversarial Learning for Detection of Clustered Microcalcifications in Mammograms
  • Sharpening Local Interpretable Model-agnostic Explanations for Histopathology: Improved Understandability and Reliability
  • Supervised Contrastive Pre-Training for Mammographic Triage Screening Models
  • Synthesis of Contrast-enhanced Spectral Mammograms from Low-energy Mammograms Using cGAN-Based Synthesis Network
  • Towards Robust Dual-view Transformation via Densifying Sparse Supervision for Mammography Lesion Matching
  • Trainable summarization to improve breast tomosynthesis classification
  • VertNet: Accurate Vertebra Localization and Identification Network from CT Images
  • Weakly-Supervised Ultrasound Video Segmentation with Minimal Annotations

    • Clinical applications - Cardiac

  • A Deep Reinforced Tree-traversal Agent for Coronary Artery Centerline Extraction
  • AnaXNet: Anatomy Aware Multi-label Finding Classification in Chest X-ray
  • AtrialGeneral: Domain Generalization for Left Atrial Segmentation of Multi-Center LGE MRIs
  • Cardiac Transmembrane Potential Imaging with GCN Based Iterative Soft Threshold Network
  • Context-aware virtual adversarial training for anatomically-plausible segmenation
  • Controllable cardiac synthesis via disentangled anatomy arithmetic
  • Cooperative Training and Latent Space Data Augmentation for Robust Medical Image Segmentation
  • DeepMitral: Fully Automatic 3D Echocardiography Segmentation for Patient Specific Mitral Valve Modelling
  • Distortion Energy for Deep Learning-based Volumetric Finite Element Mesh Generation for Aortic Valves
  • EchoCP: An Echocardiography Dataset in Contrast Transthoracic Echocardiography for Patent Foramen Ovale Diagnosis
  • EllipseNet: Anchor-Free Ellipse Detection for Automatic Cardiac Biometrics in Fetal Echocardiography
  • Fairness in Cardiac MR Image Analysis: An Investigation of Bias Due to Data Imbalance in Deep Learning Based Segmentation
  • Joint Motion Correction and Super Resolution for Cardiac Segmentation via Latent Optimisation
  • kCBAC-Net: Deeply Supervised Complete Bipartite Networks with Asymmetric Convolutions for Medical Image Segmentation
  • MT-UDA: Towards Unsupervised Cross-Modality Medical Image Segmentation with Limited Source Labels
  • Multi-frame Attention Network for Left Ventricle Segmentation in 3D Echocardiography
  • OLVA: Optimal Latent Vector Alignment for Unsupervised Domain Adaptation in Medical Image Segmentation
  • Phase-independent Latent Representation for Cardiac Shape Analysis
  • Reciprocal Learning for Semi-supervised Segmentation
  • Segmentation of Left Atrial MR Images via Self-supervised Semi-supervised Meta-learning
  • Semi-supervised Left Atrium Segmentation with Mutual Consistency Training
  • Semi-Supervised Unpaired Multi-Modal Learning for Label-Efficient Medical Image Segmentation
  • Stochastic 4D Flow Vector-Field Signatures: A new approach for comprehensive 4D Flow MRI quantification
  • Style Curriculum Learning for Robust Medical Image Segmentation
  • TEDS-Net: Enforcing Diffeomorphisms in Spatial Transformers to Guarantee Topology Preservation in Segmentations
  • Training Automatic View Planner for Cardiac MR Imaging via Self-Supervision by Spatial Relationship between Views
  • Transformer Network for Significant Stenosis Detection in CCTA of Coronary Arteries
  • TVnet: Automated Time-Resolved Tracking of the Tricuspid Valve Plane in MRI Long-Axis Cine Images with a Dual-Stage Deep Learning Pipeline
  • Ultrasound Video Transformers for Cardiac Ejection Fraction Estimation
  • UTNet: A Hybrid Transformer Architecture for Medical Image Segmentation
  • Whole Heart Mesh Generation For Image-Based Computational Simulations By Learning Free-From Deformations

    • Clinical applications - Dermatology

  • Automatic Severity Rating for Improved Psoriasis Treatment
  • Categorical Relation-Preserving Contrastive Knowledge Distillation for Medical Image Classification
  • Culprit-Prune-Net: Efficient Continual Sequential Multi-Domain Learning with Application to Skin Lesion Classification
  • End-to-end Ugly Duckling Sign Detection for Melanoma Identification with Transformers
  • FedPerl: Semi-Supervised Peer Learning for Skin Lesion Classification
  • Fighting Class Imbalance with Contrastive Learning
  • Improving the Explainability of Skin Cancer Diagnosis Using CBIR
  • Multi-level Relationship Capture Network for Automated Skin Lesion Recognition
  • Personalized Retrogress-Resilient Framework for Real-World Medical Federated Learning
  • Unsupervised Representation Learning Meets Pseudo-Label Supervised Self-Distillation: A New Approach to Rare Disease Classification

    • Clinical applications - Fetal Imaging

  • Accurate parameter estimation in fetal diffusion-weighted MRI - learning from fetal and newborn data
  • AutoFB: Automating Fetal Biometry Estimation from Standard Ultrasound Planes
  • Confidence-aware Cascaded Network for Fetal Brain Segmentation on MR Images
  • Detecting Hypo-plastic Left Heart Syndrome in Fetal Ultrasound via Disease-specific Atlas Maps
  • EllipseNet: Anchor-Free Ellipse Detection for Automatic Cardiac Biometrics in Fetal Echocardiography
  • Equivariant Filters for Efficient Tracking in 3D Imaging
  • Labels-set Loss Functions for Partial Supervision: Application to Fetal Brain 3D MRI Parcellation
  • Learning Spatiotemporal Probabilistic Atlas of Fetal Brains with Anatomically Constrained Registration Network
  • STRESS: Super-Resolution for Dynamic Fetal MRI using Self-Supervised Learning
  • Visual-Assisted Probe Movement Guidance for Obstetric Ultrasound Scanning using Landmark Retrieval

    • Clinical applications - Lung

  • 4D-CBCT Registration with a FBCT-derived Plug-and-Play Feasibility Regularizer
  • A Coherent Cooperative Learning Framework Based on Transfer Learning for Unsupervised Cross-domain Classification
  • Adversarial Domain Feature Adaptation for Bronchoscopic Depth Estimation
  • Airway Anomaly Detection by Graph Neural Network
  • AnaXNet: Anatomy Aware Multi-label Finding Classification in Chest X-ray
  • Attention based CNN-LSTM Network for Pulmonary Embolism Prediction on Chest Computed Tomography Pulmonary Angiograms
  • Attention-based Multi-scale Gated Recurrent Encoder with Novel Correlation Loss for COVID-19 Progression Prediction
  • Beyond COVID-19 Diagnosis: Prognosis with Hierarchical Graph Representation Learning
  • CA-Net: Leveraging Contextual Features for Lung Cancer Prediction
  • Chest Radiograph Disentanglement for COVID-19 Outcome Prediction
  • Detecting when pre-trained nnU-Net models fail silently for Covid-19 lung lesion segmentation
  • Determination of error in 3D CT to 2D fluoroscopy image registration for endobronchial guidance
  • Dual-Consistency Semi-Supervised Learning with Uncertainty Quantification for COVID-19 Lesion Segmentation from CT Images
  • Federated Whole Prostate Segmentation in MRI with Personalized Neural Architectures
  • Hybrid graph convolutional neural networks for anatomical segmentation
  • Improving Pneumonia Localization via Cross-Attention on Medical Images and Reports
  • Interactive smoothing parameter optimization in DBT Reconstruction using Deep learning
  • Leveraging Auxiliary Information from EMR for Weakly Supervised Pulmonary Nodule Detection
  • Longitudinal Quantitative Assessment of COVID-19 Infection Progression from Chest CTs
  • LuMiRa: An Integrated Lung Deformation Atlas and 3D-CNN model of Infiltrates for COVID-19 Prognosis
  • Lung Cancer Risk Estimation with Incomplete Data: A Joint Missing Imputation Perspective
  • M-SEAM-NAM: Multi-instance Self-supervised Equivalent Attention Mechanism with Neighborhood Affinity Module for Double Weakly Supervised Segmentation of COVID-19
  • Multimodal Multitask Deep Learning for X-Ray Image Retrieval
  • Multimodal Representation Learning via Maximization of Local Mutual Information
  • Multi-view analysis of unregistered medical images using cross-view transformers
  • OXnet: Deep Omni-supervised Thoracic Disease Detection from Chest X-rays
  • Pristine annotations-based multi-modal trained artificial intelligence solution to triage chest X-Ray for COVID19
  • RATCHET: Medical Transformer for Chest X-ray Diagnosis and Reporting
  • Refined Local-imbalance-based Weight for Airway Segmentation in CT
  • RibSeg Dataset and Strong Point Cloud Baselines for Rib Segmentation from CT Scans
  • Self-Supervised Vessel Enhancement Using Flow-Based Consistencies
  • Sequential Lung Nodule Synthesis using Attribute-guided Generative Adversarial Networks
  • USCL: Pretraining Deep Ultrasound Image Diagnosis Model through Video Contrastive Representation Learning
  • Using Causal Analysis for Conceptual Deep Learning Explanation
  • Variational Topic Inference for Chest X-Ray Report Generation

    • Clinical applications - Musculoskeletal

  • 4D-Foot: A fully automated pipeline of four-dimensional analysis of the foot bones using bi-plane X-ray video and CT
  • Acoustic-based Spatio-temporal Learning for Press-fit Evaluation of Femoral Stem Implants
  • An Interpretable Approach to Automated Severity Scoring in Pelvic Trauma
  • Automatic Path Planning for Safe Guide Pin Insertion in PCL Reconstruction Surgery
  • Increasing Consistency of Evoked Response in Thalamic Nuclei During Repetitive Burst Stimulation of Peripheral Nerve in Humans
  • Joint Spinal Centerline Extraction and Curvature Estimation with Row-wise Classification and Curve Graph Network
  • Multi-Task, Multi-Domain Deep Segmentation with Shared Representations and Contrastive Regularization for Sparse Pediatric Datasets
  • Patient-specific virtual spine straightening and vertebra inpainting: An automatic framework for osteoplasty planning
  • Revisiting contour-driven and knowledge-based deformable models: application to 2D-3D proximal femur reconstruction from X-ray images
  • RibSeg Dataset and Strong Point Cloud Baselines for Rib Segmentation from CT Scans
  • Semi-Supervised Learning for Bone Mineral Density Estimation in Hip X-ray Images
  • SpineGEM: A Hybrid-Supervised Model Generation Strategy Enabling Accurate Spine Disease Classification with a Small Training Dataset
  • Spine-Transformers: Vertebra Detection and Localization in Arbitrary Field-of-View Spine CT with Transformers
  • Towards Ultrafast MRI via Extreme k-Space Undersampling and Superresolution
  • Uncertainty Aware Deep Reinforcement Learning for Anatomical Landmark Detection in Medical Images
  • VinDr-SpineXR: A deep learning framework for spinal lesions detection and classification from radiographs

    • Clinical applications - Neuroimaging - Brain Development

  • 3D Transformer-GAN for High-quality PET Reconstruction
  • A Deep Network for Joint Registration and Parcellation of Cortical Surfaces
  • ACN: Adversarial Co-training Network for Brain Tumor Segmentation with Missing Modalities
  • Confidence-aware Cascaded Network for Fetal Brain Segmentation on MR Images
  • Covariate Correcting Networks for Identifying Associations between Socioeconomic Factors and Brain Outcomes in Children
  • Harmonization with Flow-based Causal Inference
  • Joint PVL Detection and Manual Ability Classification using Semi-Supervised Multi-task Learning
  • Labels-set Loss Functions for Partial Supervision: Application to Fetal Brain 3D MRI Parcellation
  • Learning 4D Infant Cortical Surface Atlas with Unsupervised Spherical Networks
  • Longitudinal Correlation Analysis for Decoding Multi-Modal Brain Development
  • Modality Completion via Gaussian Process Prior Variational Autoencoders for Multi-Modal Glioma Segmentation
  • Multi-site Incremental Image Quality Assessment of Structural MRI via Consensus Adversarial Representation Adaptation
  • Surface-Guided Image Fusion for Preserving Cortical Details in Human Brain Templates
  • Symmetry-Enhanced Attention Network for Acute Ischemic Infarct Segmentation with Non–Contrast CT Images
  • Temporal Feature Fusion with Sampling Pattern Optimization for Multi-echo Gradient Echo Acquisition and Image Reconstruction

    • Clinical applications - Neuroimaging - DWI and Tractography

  • A computational geometry approach for modeling neuronal fiber pathways
  • A Matrix Auto-encoder Framework to Align the Functional and Structural Connectivity Manifolds as Guided by Behavioral Phenotypes
  • A spherical convolutional neural network for white matter structure imaging via diffusion MRI
  • Accurate parameter estimation in fetal diffusion-weighted MRI - learning from fetal and newborn data
  • Active Cortex Tractography
  • Covariate Correcting Networks for Identifying Associations between Socioeconomic Factors and Brain Outcomes in Children
  • Deep Fiber Clustering: Anatomically Informed Unsupervised Deep Learning for Fast and Effective White Matter Parcellation
  • Disentangled and Proportional Representation Learning for Multi-View Brain Connectomes
  • Highly Reproducible Whole Brain Parcellation in Individuals via Voxel Annotation with Fiber Clusters
  • Q-space Conditioned Translation Networks for Directional Synthesis of Diffusion Weighted Images from Multi-modal Structural MRI
  • Quantifying structural connectivity in brain tumor patients

    • Clinical applications - Neuroimaging - Functional Brain Networks

  • A Matrix Auto-encoder Framework to Align the Functional and Structural Connectivity Manifolds as Guided by Behavioral Phenotypes
  • Building Dynamic Hierarchical Brain Networks and Capturing Transient Meta-states for Early Mild Cognitive Impairment Diagnosis
  • CarveMix: A Simple Data Augmentation Method for Brain Lesion Segmentation
  • Detecting Brain State Changes by Geometric Deep Learning of Functional Dynamics on Riemannian Manifold
  • Efficient neural network approximation of robust PCA for automated analysis of calcium imaging data
  • Estimation of spontaneous neuronal activity using homomorphic filtering
  • From Brain to Body: Learning Low-Frequency Respiration and Cardiac Signals from fMRI Dynamics
  • Inter-Regional High-level Relation Learning from Functional Connectivity via Self-Supervision
  • Meta-Modulation Network for Domain Generalization in Multi-site fMRI Classification
  • Multi-Head GAGNN: A Multi-Head Guided Attention Graph Neural Network for Modeling Spatio-Temporal Patterns of Holistic Brain Functional Networks
  • Recurrent Multigraph Integrator Network for Predicting the Evolution of Population-Driven Brain Connectivity Templates
  • Text2Brain: Synthesis of Brain Activation Maps from Free-form Text Query

    • Clinical applications - Neuroimaging - Others

  • A Deep Network for Joint Registration and Parcellation of Cortical Surfaces
  • Acceleration by deep-learnt sharing of superfluous information in multi-contrast MRI
  • Adaptive Squeeze-and-Shrink Image Denoising for Improving Deep Detection of Cerebral Microbleeds
  • Contrastive Learning with Continuous Proxy Meta-Data For 3D MRI Classification
  • Cost-Sensitive Meta-Learning for Progress Prediction of Subjective Cognitive Decline with Brain Structural MRI
  • Deep Orthogonal Fusion: Multimodal Prognostic Biomarker Discovery Integrating Radiology, Pathology, Genomic, and Clinical Data
  • Demystifying T1-MRI to FDG18-PET Image Translation via Representational Similarity
  • Estimation of spontaneous neuronal activity using homomorphic filtering
  • Imbalance-Aware Self-Supervised Learning for 3D Radiomic Representations
  • Improved Brain Lesion Segmentation with Anatomical Priors from Healthy Subjects
  • Inter Extreme Points Geodesics for End-to-End Weakly Supervised Image Segmentation
  • Intracerebral Haemorrhage Growth Prediction Based on Displacement Vector Field and Clinical Metadata
  • Learning 4D Infant Cortical Surface Atlas with Unsupervised Spherical Networks
  • LG-Net: Lesion Gate Network for Multiple Sclerosis Lesion Inpainting
  • Longitudinal self-supervision to disentangle inter-patient variability from disease progression
  • Multi-Head GAGNN: A Multi-Head Guided Attention Graph Neural Network for Modeling Spatio-Temporal Patterns of Holistic Brain Functional Networks
  • Orthogonal Ensemble Networks for Biomedical Image Segmentation
  • Personalized Matching and Analysis of Cortical Folding Patterns via Patch-Based Intrinsic Brain Mapping
  • Recurrent Multigraph Integrator Network for Predicting the Evolution of Population-Driven Brain Connectivity Templates
  • Region Ensemble Network for MCI Conversion Prediction With a Relation Regularized Loss
  • Rician noise estimation for 3D Magnetic Resonance Images based on Benford's Law
  • Scalable, Axiomatic Explanations of Deep Alzheimer's Diagnosis from Heterogeneous Data
  • SegRecon: Learning Joint Brain Surface Reconstruction and Segmentation from Images
  • Self-supervised Lesion Change Detection and Localisation in Longitudinal Multiple Sclerosis Brain Imaging
  • Self-Supervised Longitudinal Neighbourhood Embedding
  • Surface-Guided Image Fusion for Preserving Cortical Details in Human Brain Templates
  • SyNCCT: Synthetic Non-Contrast Images of the Brain from Single-Energy Computed Tomography Angiography
  • Topological Receptive Field Model for Human Retinotopic Mapping
  • Towards Ultrafast MRI via Extreme k-Space Undersampling and Superresolution

    • Clinical applications - Oncology

  • A Location Constrained Dual-branch Network for Reliable Diagnosis of Jaw Tumors and Cysts
  • AMINN: Autoencoder-based Multiple Instance Neural Network Improves Outcome Prediction of Multifocal Liver Metastases
  • Beyond Non-Maximum Suppression - Detecting Lesions in Digital Breast Tomosynthesis Volumes
  • Coarse-to-fine Segmentation of Organs at Risk in Nasopharyngeal Carcinoma Radiotherapy
  • Co-Graph Attention Reasoning based Imaging and Clinical Features Integration for Lymph Node Metastasis Prediction
  • Continuous-Time Deep Glioma Growth Models
  • Deep Orthogonal Fusion: Multimodal Prognostic Biomarker Discovery Integrating Radiology, Pathology, Genomic, and Clinical Data
  • DeepStationing: Thoracic Lymph Node Station Parsing in CT Scans using Anatomical Context Encoding and Key Organ Auto-Search
  • Do we need complex image features to personalize treatment of patients with locally advanced rectal cancer?
  • Efficient Semi-Supervised Gross Target Volume of Nasopharyngeal Carcinoma Segmentation via Uncertainty Rectified Pyramid Consistency
  • From Pixel to Whole Slide: Automatic Detection of Microvascular Invasion in Hepatocellular Carcinoma on Histopathological Image via Cascaded Networks
  • Hepatocellular Carcinoma Segmentation from Digital Subtraction Angiography Videos using Learnable Temporal Difference
  • Hierarchical Attention Guided Framework for Multi-resolution Collaborative Whole Slide Image Segmentation
  • Hierarchical Phenotyping and Graph Modeling of Spatial Architecture in Lymphoid Neoplasms
  • High-particle simulation of Monte-Carlo dose distribution with 3D ConvLSTMs
  • HRENet: A Hard Region Enhancement Network for Polyp Segmentation
  • hSDB-instrument: Instrument Localization Database for Laparoscopic and Robotic Surgeries
  • Incorporating Isodose Lines and Gradient Information via Multi-task Learning for Dose Prediction in Radiotherapy
  • Motion Correction for Liver DCE-MRI with Time-Intensity Curve Constraint
  • Multiple Instance Learning with Auxiliary Task Weighting for Multiple Myeloma Classification
  • Orthogonal Ensemble Networks for Biomedical Image Segmentation
  • Parallel Capsule Networks for Classification of White Blood Cells
  • Personalized Respiratory Motion Model Using Conditional Generative Networks for MR-Guided Radiotherapy
  • Predicting Esophageal Fistula Risks Using a Multimodal Self-Attention Network
  • Predicting Symptoms from Multiphasic MRI via Multi-Instance Attention Learning for Hepatocellular Carcinoma Grading
  • Quantifying structural connectivity in brain tumor patients
  • Rapid treatment planning for low-dose-rate prostate brachytherapy with TP-GAN
  • SA-GAN: Structure-Aware GAN for Organ-Preserving Synthetic CT Generation
  • Sequential Learning on Liver Tumor Boundary Semantics and Prognostic Biomarker Mining
  • Whole Slide Images are 2D Point Clouds: Context-Aware Survival Prediction using Patch-based Graph Convolutional Networks

    • Clinical applications - Ophthalmology

  • A Line to Align: Deep Dynamic Time Warping for Retinal OCT Segmentation
  • A Multi-Branch Hybrid Transformer Network for Corneal Endothelial Cell Segmentation
  • Balanced-MixUp for highly imbalanced medical image classification
  • BSDA-Net: A Boundary Shape and Distance Aware Joint Learning Framework for Segmenting and Classifying OCTA Images
  • CataNet: Predicting remaining cataract surgery duration
  • Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images
  • Distinguishing Differences Matters: Focal Contrastive Network for Peripheral Anterior Synechiae Recognition
  • Effective semantic segmentation in Cataract surgery: What matters most?
  • Estimation of High Frame Rate Digital Subtraction Angiography Sequences at Low Radiation Dose
  • Few-shot Transfer Learning for Hereditary Retinal Diseases Recognition
  • Fighting Class Imbalance with Contrastive Learning
  • Interpretable gender classification from retinal fundus images using BagNets
  • I-SECRET: Importance-guided fundus image enhancement via semi-supervised contrastive constraining
  • Learning to Address Intra-segment Misclassification in Retinal Imaging
  • LensID: A CNN-RNN-Based Framework Towards Lens Irregularity Detection in Cataract Surgery Videos
  • LIFE: A Generalizable Autodidactic Pipeline for 3D OCT-A Vessel Segmentation
  • Local-global Dual Perception based Deep Multiple Instance Learning for Retinal Disease Classification
  • MIL-VT: Multiple Instance Learning Enhanced Vision Transformer for Fundus Image Classification
  • Projective Skip-Connections for Segmentation Along a Subset of Dimensions in Retinal OCT
  • Relational Subsets Knowledge Distillation for Long-tailed Retinal Diseases Recognition
  • RV-GAN: Segmenting Retinal Vascular Structure in Fundus Photographs using a Novel Multi-scale Generative Adversarial Network
  • Simultaneous Alignment and Surface Regression Using Hybrid 2D-3D Networks for 3D Coherent Layer Segmentation of Retina OCT Images
  • Source-Free Domain Adaptive Fundus Image Segmentation with Denoised Pseudo-Labeling

    • Clinical applications - Vascular

  • A Deep Learning Bidirectional Temporal Tracking Algorithm for Automated Blood Cell Counting from Non-invasive Capillaroscopy Videos
  • Adaptive Squeeze-and-Shrink Image Denoising for Improving Deep Detection of Cerebral Microbleeds
  • Deep Open Snake Tracker for Vessel Tracing
  • Joint Segmentation and Quantification of Main Coronary Vessels Using Dual-branch Multi-scale Attention Network
  • LIFE: A Generalizable Autodidactic Pipeline for 3D OCT-A Vessel Segmentation
  • MASC-Units: Training Oriented Filters for Segmenting Curvilinear Structures
  • Multimodal Sensing Guidewire for C-arm Navigation with Random UV Enhanced Optical Sensors using Spatio-temporal Networks
  • Noisy Labels are Treasure: Mean-Teacher-Assisted Confident Learning for Hepatic Vessel Segmentation
  • Renal Cell Carcinoma Classification from Vascular Morphology
  • Self-Supervised Vessel Enhancement Using Flow-Based Consistencies
  • Stochastic 4D Flow Vector-Field Signatures: A new approach for comprehensive 4D Flow MRI quantification
  • SyNCCT: Synthetic Non-Contrast Images of the Brain from Single-Energy Computed Tomography Angiography
  • Vessel Width Estimation via Convolutional Regression

    • Computational (Integrative) Pathology

  • A computational geometry approach for modeling neuronal fiber pathways
  • Accounting for Dependencies in Deep Learning based Multiple Instance Learning for Whole Slide Imaging
  • Adversarial learning of cancer tissue representations
  • Automated Malaria Cells Detection from Blood Smears under Severe Class Imbalance via Importance-aware Balanced Group Softmax
  • Cells are Actors: Social Network Analysis with Classical ML for SOTA Histology Image Classification
  • DT-MIL: Deformable Transformer for Multi-instance Learning on Histopathological Image
  • Early Detection of Liver Fibrosis Using Graph Convolutional Networks
  • Focusing on Clinically Interpretable Features: Selective Attention Regularization for Liver Biopsy Image Classification
  • From Pixel to Whole Slide: Automatic Detection of Microvascular Invasion in Hepatocellular Carcinoma on Histopathological Image via Cascaded Networks
  • Generalizing Nucleus Recognition Model in Multi-source Ki67 Immunohistochemistry Stained Images via Domain-specific Pruning
  • GQ-GCN: Group Quadratic Graph Convolutional Network for Classification of Histopathological Images
  • Hierarchical Attention Guided Framework for Multi-resolution Collaborative Whole Slide Image Segmentation
  • Hierarchical graph pathomic network for progression free survival prediction
  • Hierarchical Phenotyping and Graph Modeling of Spatial Architecture in Lymphoid Neoplasms
  • Hybrid Supervision Learning for Whole Slide Image Classification
  • Increasing Consistency of Evoked Response in Thalamic Nuclei During Repetitive Burst Stimulation of Peripheral Nerve in Humans
  • Instance-aware Feature Alignment for Cross-domain Cell Nuclei Detection in Histopathology Images
  • Instance-based Vision Transformer for Subtyping of Papillary Renal Cell Carcinoma in Histopathological Image
  • Integration of Patch Features through Self-Supervised Learning and Transformer for Survival Analysis on Whole Slide Images
  • Learning More for Free - A Multi Task Learning Approach for Improved Pathology Classification in Capsule Endoscopy
  • Learning Visual Features by Colorization for Slide-Consistent Survival Prediction from Whole Slide Images
  • MetaCon: Meta Contrastive Learning for Microsatellite Instability Detection
  • MorphSet: Improving Renal Histopathology Case Assessment Through Learned Prognostic Vectors
  • Nuclei Grading of Clear Cell Renal Cell Carcinoma in Histopathological Image by Composite High-Resolution Network
  • Parallel Capsule Networks for Classification of White Blood Cells
  • Pay Attention with Focus: A Novel Learning Scheme for Classification of Whole Slide Images
  • Positive-unlabeled Learning for Cell Detection in Histopathology Images with Incomplete Annotations
  • Primary Tumor and Inter-Organ Augmentations for Supervised Lymph Node Colon Adenocarcinoma Metastasis Detection
  • Prototypical models for classifying high-risk atypical breast lesions
  • Ranking loss: A ranking-based deep neural network for colorectal cancer grading in pathology images
  • Self-supervised visual representation learning for histopathological images
  • Semi-supervised Adversarial Learning for Stain Normalisation in Histopathology Images
  • Sequential Gaussian Process Regression for Simultaneous Pathology Detection and Shape Reconstruction
  • SimTriplet: Simple Triplet Representation Learning with a Single GPU
  • SSLP: Spatial Guided Self-supervised Learning on Pathological Images
  • Stain Mix-up: Unsupervised Domain Generalization for Histopathology Images
  • Structure-Preserving Multi-Domain Stain Color Augmentation using Style-Transfer with Disentangled Representations
  • Survival Prediction Based on Histopathology Imaging and Clinical Data: A Novel, Whole Slide CNN Approach
  • TransPath: Transformer-based Self-supervised Learning for Histopathological Image Classification
  • Weakly supervised pan-cancer segmentation tool
  • Whole Slide Images are 2D Point Clouds: Context-Aware Survival Prediction using Patch-based Graph Convolutional Networks

    • Computational Anatomy and Physiology

  • A Deep Learning Bidirectional Temporal Tracking Algorithm for Automated Blood Cell Counting from Non-invasive Capillaroscopy Videos
  • Automating Embryo Development Stage Detection in Time-Lapse Imaging with Synergic Loss and Temporal Learning
  • Bayesian Atlas Building with Hierarchical Priors for Subject-specific Regularization
  • Deep Open Snake Tracker for Vessel Tracing
  • Exploring the Functional Difference of Gyri/Sulci via Hierarchical Interpretable Autoencoder
  • Hybrid graph convolutional neural networks for anatomical segmentation
  • Implicit Neural Distance Representation for Unsupervised and Supervised Classification of Complex Anatomies
  • Increasing Consistency of Evoked Response in Thalamic Nuclei During Repetitive Burst Stimulation of Peripheral Nerve in Humans
  • Local Morphological Measures Confirm that Folding within Small Partitions of the Human Cortex Follows Universal Scaling Law
  • Longitudinal self-supervision to disentangle inter-patient variability from disease progression
  • Multi-Task, Multi-Domain Deep Segmentation with Shared Representations and Contrastive Regularization for Sparse Pediatric Datasets
  • Phase-independent Latent Representation for Cardiac Shape Analysis
  • Spine-Transformers: Vertebra Detection and Localization in Arbitrary Field-of-View Spine CT with Transformers
  • Stochastic 4D Flow Vector-Field Signatures: A new approach for comprehensive 4D Flow MRI quantification
  • Topological Receptive Field Model for Human Retinotopic Mapping
  • Whole Heart Mesh Generation For Image-Based Computational Simulations By Learning Free-From Deformations

    • Computer Aided Diagnosis

  • 3D Brain Midline Delineation for Hematoma Patients
  • A Coherent Cooperative Learning Framework Based on Transfer Learning for Unsupervised Cross-domain Classification
  • A Deep Reinforced Tree-traversal Agent for Coronary Artery Centerline Extraction
  • A Line to Align: Deep Dynamic Time Warping for Retinal OCT Segmentation
  • A Location Constrained Dual-branch Network for Reliable Diagnosis of Jaw Tumors and Cysts
  • A Segmentation-Assisted Model for Universal Lesion Detection with Partial Labels
  • Accounting for Dependencies in Deep Learning based Multiple Instance Learning for Whole Slide Imaging
  • Adaptive Squeeze-and-Shrink Image Denoising for Improving Deep Detection of Cerebral Microbleeds
  • Airway Anomaly Detection by Graph Neural Network
  • Alleviating Data Imbalance Issue with Perturbed Input during Inference
  • AMINN: Autoencoder-based Multiple Instance Neural Network Improves Outcome Prediction of Multifocal Liver Metastases
  • An Interpretable Approach to Automated Severity Scoring in Pelvic Trauma
  • AnaXNet: Anatomy Aware Multi-label Finding Classification in Chest X-ray
  • Asymmetric 3D Context Fusion for Universal Lesion Detection
  • Attention based CNN-LSTM Network for Pulmonary Embolism Prediction on Chest Computed Tomography Pulmonary Angiograms
  • Attention-based Multi-scale Gated Recurrent Encoder with Novel Correlation Loss for COVID-19 Progression Prediction
  • AutoFB: Automating Fetal Biometry Estimation from Standard Ultrasound Planes
  • Automated Malaria Cells Detection from Blood Smears under Severe Class Imbalance via Importance-aware Balanced Group Softmax
  • Automating Embryo Development Stage Detection in Time-Lapse Imaging with Synergic Loss and Temporal Learning
  • Balanced-MixUp for highly imbalanced medical image classification
  • Beyond Non-Maximum Suppression - Detecting Lesions in Digital Breast Tomosynthesis Volumes
  • BI-RADS Classification of Calcification on Mammograms
  • CA-Net: Leveraging Contextual Features for Lung Cancer Prediction
  • Categorical Relation-Preserving Contrastive Knowledge Distillation for Medical Image Classification
  • Cells are Actors: Social Network Analysis with Classical ML for SOTA Histology Image Classification
  • Chest Radiograph Disentanglement for COVID-19 Outcome Prediction
  • Co-Graph Attention Reasoning based Imaging and Clinical Features Integration for Lymph Node Metastasis Prediction
  • Collaborative Image Synthesis and Disease Diagnosis for Classification of Neurodegenerative Disorders with Incomplete Multi-modal Neuroimages
  • Colorectal Polyp Classification from White-light Colonoscopy Images via Domain Alignment
  • Combining 3D Image and Tabular Data via the Dynamic Affine Feature Map Transform
  • Combining Attention-based Multiple Instance Learning and Gaussian Processes for CT Hemorrhage Detection
  • Comprehensive Importance-based Selective Regularization for Continual Segmentation Across Multiple Sites
  • Conditional GAN with an Attention-based Generator and a 3D Discriminator for 3D Medical Image Generation
  • Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images
  • Context-aware virtual adversarial training for anatomically-plausible segmenation
  • Continual Learning with Bayesian Model based on a Fixed Pre-trained Feature Extractor
  • Contrastive Learning with Continuous Proxy Meta-Data For 3D MRI Classification
  • Contrastive Pre-training and Representation Distillation for Medical Visual Question Answering Based on Radiology Images
  • Cost-Sensitive Meta-Learning for Progress Prediction of Subjective Cognitive Decline with Brain Structural MRI
  • DAE-GCN: Identifying Disease-Related Features for Disease Prediction
  • Data Augmentation in Logit Space for Medical Image Classification with Limited Training Data
  • Deep Neural Dynamic Bayesian Networks applied to EEG sleep spindles modeling
  • DeepMitral: Fully Automatic 3D Echocardiography Segmentation for Patient Specific Mitral Valve Modelling
  • DeepOPG: Improving Orthopantomogram Finding Summarization with Weak Supervision
  • Depth Estimation for Colonoscopy Images with Self-supervised Learning from Videos
  • Detecting Outliers with Poisson Image Interpolation
  • DLLNet: An Attention-based Deep Learning Method for Dental Landmark Localization on High-Resolution 3D Digital Dental Models
  • Dual-Consistency Semi-Supervised Learning with Uncertainty Quantification for COVID-19 Lesion Segmentation from CT Images
  • Effective Pancreatic Cancer Screening on Non-contrast CT Scans via Anatomy-Aware Transformers
  • Efficient and Generic Interactive Segmentation Framework to Correct Mispredictions during Clinical Evaluation of Medical Images
  • EndoUDA: A modality independent segmentation approach for endoscopy imaging
  • End-to-end Ugly Duckling Sign Detection for Melanoma Identification with Transformers
  • Energy-Based Supervised Hashing for Multimorbidity Image Retrieval
  • Enhanced Breast Lesion Classification via Knowledge Guided Cross-Modal and Semantic Data Augmentation
  • Explaining COVID-19 and Thoracic Pathology Model Predictions by Identifying Informative Input Features
  • Facial and cochlear nerves characterization using deep reinforcement learning for landmark detection
  • Federated Contrastive Learning for Decentralized Unlabeled Medical Images
  • Federated Semi-supervised Medical Image Classification via Inter-client Relation Matching
  • FedPerl: Semi-Supervised Peer Learning for Skin Lesion Classification
  • Few Trust Data Guided Annotation Refinement for Upper Gastrointestinal Anatomy Recognition
  • Few-shot Transfer Learning for Hereditary Retinal Diseases Recognition
  • Focusing on Clinically Interpretable Features: Selective Attention Regularization for Liver Biopsy Image Classification
  • From Pixel to Whole Slide: Automatic Detection of Microvascular Invasion in Hepatocellular Carcinoma on Histopathological Image via Cascaded Networks
  • Hepatocellular Carcinoma Segmentation from Digital Subtraction Angiography Videos using Learnable Temporal Difference
  • Hierarchical graph pathomic network for progression free survival prediction
  • Hierarchical Phenotyping and Graph Modeling of Spatial Architecture in Lymphoid Neoplasms
  • High-Resolution Hierarchical Adversarial Learning for OCT Speckle Noise Reduction
  • HRENet: A Hard Region Enhancement Network for Polyp Segmentation
  • Hybrid Supervision Learning for Whole Slide Image Classification
  • Instance-based Vision Transformer for Subtyping of Papillary Renal Cell Carcinoma in Histopathological Image
  • Integration of Patch Features through Self-Supervised Learning and Transformer for Survival Analysis on Whole Slide Images
  • Interactive smoothing parameter optimization in DBT Reconstruction using Deep learning
  • Joint PVL Detection and Manual Ability Classification using Semi-Supervised Multi-task Learning
  • Joint Segmentation and Quantification of Main Coronary Vessels Using Dual-branch Multi-scale Attention Network
  • Joint Spinal Centerline Extraction and Curvature Estimation with Row-wise Classification and Curve Graph Network
  • LambdaUNet: 2.5D Stroke Lesion Segmentation of Diffusion-weighted MR Images
  • LDPolypVideo Benchmark: A Large-scale Colonoscopy Video Dataset of Diverse Polyps
  • Learned super resolution ultrasound for improved breast lesion characterization
  • Learning from Subjective Ratings Using Auto-Decoded Deep Latent Embeddings
  • Learning More for Free - A Multi Task Learning Approach for Improved Pathology Classification in Capsule Endoscopy
  • Learning-based attenuation quantification in abdominal ultrasound
  • Lesion Segmentation and RECIST Diameter Prediction via Click-driven Attention and Dual-path Connection
  • Lesion-based Contrastive Learning for Diabetic Retinopathy Grading from Fundus Images
  • Linear Prediction Residual for Efficient Diagnosis of Parkinson's Disease from Gait
  • MBFF-Net: Multi-Branch Feature Fusion Network for Carotid Plaque Segmentation in Ultrasound
  • Meta-Modulation Network for Domain Generalization in Multi-site fMRI Classification
  • mfTrans-Net: Quantitative Measurement of Hepatocellular Carcinoma via Multi-Function Transformer Regression Network
  • MG-NET: Leveraging Pseudo-Imaging for Multi-Modal Metagenome Analysis
  • Motion Correction for Liver DCE-MRI with Time-Intensity Curve Constraint
  • MT-UDA: Towards Unsupervised Cross-Modality Medical Image Segmentation with Limited Source Labels
  • Multi-Compound Transformer for Accurate Biomedical Image Segmentation
  • Multi-frame Collaboration for Effective Endoscopic Video Polyp Detection via Spatial-Temporal Feature Transformation
  • Multi-level Relationship Capture Network for Automated Skin Lesion Recognition
  • Multimodal Multitask Deep Learning for X-Ray Image Retrieval
  • Multiple Instance Learning with Auxiliary Task Weighting for Multiple Myeloma Classification
  • Multiple Meta-model Quantifying for Medical Visual Question Answering
  • Multi-Task, Multi-Domain Deep Segmentation with Shared Representations and Contrastive Regularization for Sparse Pediatric Datasets
  • Multi-view analysis of unregistered medical images using cross-view transformers
  • Neighbor Matching for Semi-supervised Learning
  • nnDetection: A Self-configuring Method for Medical Object Detection
  • Noisy Labels are Treasure: Mean-Teacher-Assisted Confident Learning for Hepatic Vessel Segmentation
  • Non-invasive Assessment of Hepatic Venous Pressure Gradient (HVPG) Based on MR Flow Imaging and Computational Fluid Dynamics
  • Nuclei Grading of Clear Cell Renal Cell Carcinoma in Histopathological Image by Composite High-Resolution Network
  • Parallel Capsule Networks for Classification of White Blood Cells
  • Personalized Retrogress-Resilient Framework for Real-World Medical Federated Learning
  • Positive-unlabeled Learning for Cell Detection in Histopathology Images with Incomplete Annotations
  • Predicting Esophageal Fistula Risks Using a Multimodal Self-Attention Network
  • Predicting Symptoms from Multiphasic MRI via Multi-Instance Attention Learning for Hepatocellular Carcinoma Grading
  • Primary Tumor and Inter-Organ Augmentations for Supervised Lymph Node Colon Adenocarcinoma Metastasis Detection
  • Projection-wise Disentangling for Fair and Interpretable Representation Learning: Application to 3D Facial Shape Analysis
  • Prototypical models for classifying high-risk atypical breast lesions
  • Radiomics-informed Deep Curriculum Learning for Breast Cancer Diagnosis
  • Recurrent Multigraph Integrator Network for Predicting the Evolution of Population-Driven Brain Connectivity Templates
  • Region Ensemble Network for MCI Conversion Prediction With a Relation Regularized Loss
  • Retina-Match: Ipsilateral Mammography Lesion Matching in a Single Shot Detection Pipeline
  • RV-GAN: Segmenting Retinal Vascular Structure in Fundus Photographs using a Novel Multi-scale Generative Adversarial Network
  • SA-GAN: Structure-Aware GAN for Organ-Preserving Synthetic CT Generation
  • Seg4Reg+: A Local and Global ConsistencyLearning between Spine Segmentation and CobbAngle Regression
  • Self-supervised Lesion Change Detection and Localisation in Longitudinal Multiple Sclerosis Brain Imaging
  • Self-supervised visual representation learning for histopathological images
  • Semi-Supervised Learning for Bone Mineral Density Estimation in Hip X-ray Images
  • Sequential Gaussian Process Regression for Simultaneous Pathology Detection and Shape Reconstruction
  • Sharpening Local Interpretable Model-agnostic Explanations for Histopathology: Improved Understandability and Reliability
  • Source-Free Domain Adaptive Fundus Image Segmentation with Denoised Pseudo-Labeling
  • SPARTA: An Integrated Stability, Discriminability, and Sparsity based Radiomic Feature Selection Approach
  • Stochastic 4D Flow Vector-Field Signatures: A new approach for comprehensive 4D Flow MRI quantification
  • Supervised Contrastive Pre-Training for Mammographic Triage Screening Models
  • Symmetry-Enhanced Attention Network for Acute Ischemic Infarct Segmentation with Non–Contrast CT Images
  • Tensor-based Multi-index Representation Learning for Major Depression Disorder Detection with Resting-state fMRI
  • Towards a non-invasive diagnosis of portal hypertension based on an Eulerian CFD model with diffuse boundary conditions
  • Towards Robust Dual-view Transformation via Densifying Sparse Supervision for Mammography Lesion Matching
  • Towards Semantic Interpretation of Thoracic Disease and COVID-19 Diagnosis Models
  • Transfer Learning of Deep Spatiotemporal Networks to Model Arbitrarily Long Videos of Seizures
  • Triplet-Branch Network with Prior-Knowledge Embedding for Fatigue Fracture Grading
  • Ultrasound Video Transformers for Cardiac Ejection Fraction Estimation
  • Uncertainty Aware Deep Reinforcement Learning for Anatomical Landmark Detection in Medical Images
  • Unsupervised Contrastive Learning of Radiomics and Deep Features for Label-Efficient Tumor Classification
  • Unsupervised Representation Learning Meets Pseudo-Label Supervised Self-Distillation: A New Approach to Rare Disease Classification
  • USCL: Pretraining Deep Ultrasound Image Diagnosis Model through Video Contrastive Representation Learning
  • Using Causal Analysis for Conceptual Deep Learning Explanation
  • VertNet: Accurate Vertebra Localization and Identification Network from CT Images
  • Vessel Width Estimation via Convolutional Regression
  • Weakly-Supervised Universal Lesion Segmentation with Regional Level Set Loss
  • Whole Heart Mesh Generation For Image-Based Computational Simulations By Learning Free-From Deformations
  • You Only Learn Once: Universal Anatomical Landmark Detection

    • Image Reconstruction

  • 2.5D Thermometry Maps for MRI-guided Tumor Ablation
  • A Data-driven Approach for High Frame Rate Synthetic Transmit Aperture Ultrasound Imaging
  • A Neural Framework for Multi-Variable Lesion Quantification Through B-mode Style Transfer
  • Acceleration by deep-learnt sharing of superfluous information in multi-contrast MRI
  • Adaptive Squeeze-and-Shrink Image Denoising for Improving Deep Detection of Cerebral Microbleeds
  • Cardiac Transmembrane Potential Imaging with GCN Based Iterative Soft Threshold Network
  • Conditional GAN with an Attention-based Generator and a 3D Discriminator for 3D Medical Image Generation
  • Cross-domain Depth Estimation Network for 3D Vessel Reconstruction in OCT Angiography
  • DA-VSR: Domain Adaptable Volumetric Super-Resolution For Medical Images
  • Deep J-Sense: Accelerated MRI Reconstruction via Unrolled Alternating Optimization
  • Depth Estimation for Colonoscopy Images with Self-supervised Learning from Videos
  • Disentangled Sequential Graph Autoencoder for Preclinical Alzheimer's Disease Characterizations from ADNI Study
  • Dual-Domain Adaptive-Scaling Non-Local Network for CT Metal Artifact Reduction
  • Fast Magnetic Resonance Imaging on Regions of Interest: From Sensing to Reconstruction
  • Generalised Super Resolution for Quantitative MRI Using Self-Supervised Mixture of Experts
  • Generator Versus Segmentor: Pseudo-healthy Synthesis
  • High-Resolution Hierarchical Adversarial Learning for OCT Speckle Noise Reduction
  • High-resolution segmentation of lumbar vertebrae from conventional thick slice MRI
  • Improving Generalizability in Limited-Angle CT Reconstruction with Sinogram Extrapolation
  • InDuDoNet: An Interpretable Dual Domain Network for CT Metal Artifact Reduction
  • Interactive smoothing parameter optimization in DBT Reconstruction using Deep learning
  • Interpretable deep learning for multimodal super-resolution of medical images
  • IREM: High-Resolution Magnetic Resonance Image Reconstruction via Implicit Neural Representation
  • I-SECRET: Importance-guided fundus image enhancement via semi-supervised contrastive constraining
  • Joint Optimization of Hadamard Sensing and Reconstruction in Compressed Sensing Fluorescence Microscopy
  • Label-Free Physics-Informed Image Sequence Reconstruction with Disentangled Spatial-Temporal Modeling
  • Learnable Multi-scale Fourier Interpolation for Sparse View CT Image Reconstruction
  • Learning to Predict Error for MRI Reconstruction
  • Learning-based attenuation quantification in abdominal ultrasound
  • Memory-efficient Learning for High-dimensional MRI Reconstruction
  • MouseGAN: GAN-Based Multiple MRI Modalities Synthesis and Segmentation for Mouse Brain Structures
  • MRI Super-Resolution Through Generative Degradation Learning
  • Multi-Contrast MRI Super-Resolution via a Multi-Stage Integration Network
  • Multimodal MRI Acceleration via Deep Cascading Networks with Peer-layer-wise Dense Connections
  • Noise Mapping and Removal in Complex-Valued Multi-Channel MRI via Optimal Shrinkage of Singular Values
  • Over-and-Under Complete Convolutional RNN for MRI Reconstruction
  • Patch-Free 3D Medical Image Segmentation Driven by Super-Resolution Technique and Self-Supervised Guidance
  • Personalized CT Organ Dose Estimation from Scout Images
  • Real-Time Mapping of Tissue Properties for Magnetic Resonance Fingerprinting
  • Rician noise estimation for 3D Magnetic Resonance Images based on Benford's Law
  • RLP-Net: Recursive Light Propagation Network for 3-D Virtual Refocusing
  • SA-GAN: Structure-Aware GAN for Organ-Preserving Synthetic CT Generation
  • Self Context and Shape Prior for Sensorless Freehand 3D Ultrasound Reconstruction
  • Self-Supervised Learning for MRI Reconstruction with a Parallel Network Training Framework
  • Self-supervised visual representation learning for histopathological images
  • Sequential Lung Nodule Synthesis using Attribute-guided Generative Adversarial Networks
  • Synthesizing Multi-Tracer PET Images for Alzheimer's Disease Patients using a 3D Unified Anatomy-aware Cyclic Adversarial Network
  • TarGAN: Target-Aware Generative Adversarial Networks for Multi-modality Medical Image Translation
  • Task Transformer Network for Joint MRI Reconstruction and Super-Resolution
  • Temporal Feature Fusion with Sampling Pattern Optimization for Multi-echo Gradient Echo Acquisition and Image Reconstruction
  • Towards Ultrafast MRI via Extreme k-Space Undersampling and Superresolution
  • TransCT: Dual-path Transformer for Low Dose Computed Tomography
  • Two-Stage Self-Supervised Cycle-Consistency Network for Reconstruction of Thin-Slice MR Images
  • U-DuDoNet: Unpaired dual-domain network for CT metal artifact reduction
  • Universal Undersampled MRI Reconstruction
  • Unsupervised Network Learning for Cell Segmentation

    • Image Registration

  • 4D-CBCT Registration with a FBCT-derived Plug-and-Play Feasibility Regularizer
  • 4D-Foot: A fully automated pipeline of four-dimensional analysis of the foot bones using bi-plane X-ray video and CT
  • A Deep Discontinuity-Preserving Image Registration Network
  • A Deep Network for Joint Registration and Parcellation of Cortical Surfaces
  • Atlas-Based Segmentation of Intracochlear Anatomy in Metal Artifact Affected CT Images of the Ear with Co-trained Deep Neural Networks
  • Bayesian Atlas Building with Hierarchical Priors for Subject-specific Regularization
  • Conditional Deformable Image Registration with Convolutional Neural Network
  • Construction of Longitudinally Consistent 4D Infant Cerebellum Atlases based on Deep Learning
  • Cross-modal Attention for MRI and Ultrasound Volume Registration
  • Deep Iterative 2D/3D Registration
  • Determination of error in 3D CT to 2D fluoroscopy image registration for endobronchial guidance
  • End-to-end Ultrasound Frame to Volume Registration
  • Equivariant Filters for Efficient Tracking in 3D Imaging
  • GloFlow: Whole Slide Image Stitching from Video using Optical Flow and Global Image Alignment
  • Image-based Incision Detection for Topological Intraoperative 3D Model Update in Augmented Reality Assisted Laparoscopic Surgery
  • Image-to-Graph Convolutional Network for Deformable Shape Reconstruction from a Single Projection Image
  • Learning 4D Infant Cortical Surface Atlas with Unsupervised Spherical Networks
  • Learning Dual Transformer Network for Diffeomorphic Registration
  • Learning Spatiotemporal Probabilistic Atlas of Fetal Brains with Anatomically Constrained Registration Network
  • Learning Unsupervised Parameter-specific Affine Transformation for Medical Images Registration
  • Medical Image Registration Based on Uncoupled Learning and Accumulative Enhancement
  • Motion Correction for Liver DCE-MRI with Time-Intensity Curve Constraint
  • Multi-scale Neural ODEs for 3D Medical Image Registration
  • Nesterov Accelerated ADMM for Fast Diffeomorphic Image Registration
  • Patient-specific virtual spine straightening and vertebra inpainting: An automatic framework for osteoplasty planning
  • Real-Time Rotated Convolutional Descriptor for Surgical Environments
  • Revisiting iterative highly efficient optimisation schemes in medical image registration
  • SAME: Deformable Image Registration based on Self-supervised Anatomical Embeddings
  • Self-Supervised Multi-Modal Alignment For Whole Body Medical Imaging
  • Spectral Embedding Approximation and Descriptor Learning for Craniofacial Volumetric Image Correspondence
  • Surface-Guided Image Fusion for Preserving Cortical Details in Human Brain Templates
  • Unsupervised Diffeomorphic Surface Registration and Non-Linear Modelling
  • Using Multiple Images and Contours for Deformable 3D-2D Registration of a Preoperative CT in Laparoscopic Liver Surgery
  • Weakly Supervised Registration of Prostate MRI and Histopathology Images

    • Image Segmentation

  • 2D Histology Meets 3D Topology: Cytoarchitectonic Brain Mapping with Graph Neural Networks
  • 3D Brain Midline Delineation for Hematoma Patients
  • 3D Graph-S2Net: Shape-Aware Self-Ensembling Network for Semi-Supervised Segmentation with Bilateral Graph Convolution
  • 3D-UCaps: 3D Capsules Unet for Volumetric Image Segmentation
  • 4D-Foot: A fully automated pipeline of four-dimensional analysis of the foot bones using bi-plane X-ray video and CT
  • A Deep Network for Joint Registration and Parcellation of Cortical Surfaces
  • A hybrid attention ensemble framework for zonal prostate segmentation
  • A Line to Align: Deep Dynamic Time Warping for Retinal OCT Segmentation
  • A Location Constrained Dual-branch Network for Reliable Diagnosis of Jaw Tumors and Cysts
  • A Multi-Branch Hybrid Transformer Network for Corneal Endothelial Cell Segmentation
  • A Novel Hybrid Convolutional Neural Network for Accurate Organ Segmentation in 3D Head and Neck CT Images
  • A Spatial Guided Self-supervised Clustering Network for Medical Image Segmentation
  • A Topological-Attention ConvLSTM Network and Its Application to EM Images
  • ACN: Adversarial Co-training Network for Brain Tumor Segmentation with Missing Modalities
  • Anatomy of Domain Shift Impact on U-Net Layers in MRI Segmentation
  • Anatomy-Constrained Contrastive Learning for Synthetic Segmentation without Ground-truth
  • ASC-Net: Adversarial-based Selective Network for Unsupervised Anomaly Segmentation
  • Atlas-Based Segmentation of Intracochlear Anatomy in Metal Artifact Affected CT Images of the Ear with Co-trained Deep Neural Networks
  • AtrialGeneral: Domain Generalization for Left Atrial Segmentation of Multi-Center LGE MRIs
  • AutoFB: Automating Fetal Biometry Estimation from Standard Ultrasound Planes
  • Automatic Path Planning for Safe Guide Pin Insertion in PCL Reconstruction Surgery
  • Automatic Polyp Segmentation via Multi-scale Subtraction Network
  • AxonEM Dataset: 3D Axon Instance Segmentation of Brain Cortical Regions
  • BiX-NAS: Searching Efficient Bi-directional Architecture for Medical Image Segmentation
  • Boundary-aware Transformers for Skin Lesion Segmentation
  • Bounding Box Tightness Prior for Weakly Supervised Image Segmentation
  • BSDA-Net: A Boundary Shape and Distance Aware Joint Learning Framework for Segmenting and Classifying OCTA Images
  • CA^{2.5}-Net Nuclei Segmentation Framework with a Microscopy Cell Benchmark Collection
  • CarveMix: A Simple Data Augmentation Method for Brain Lesion Segmentation
  • CCBANet: Cascading Context and Balancing Attention for Polyp Segmentation
  • Coarse-to-fine Segmentation of Organs at Risk in Nasopharyngeal Carcinoma Radiotherapy
  • Co-Generation and Segmentation for Generalized Surgical Instrument Segmentation on Unlabelled Data
  • Comprehensive Importance-based Selective Regularization for Continual Segmentation Across Multiple Sites
  • Conditional GAN with an Attention-based Generator and a 3D Discriminator for 3D Medical Image Generation
  • Conditional Training with Bounding Map for Universal Lesion Detection
  • Confidence-aware Cascaded Network for Fetal Brain Segmentation on MR Images
  • Consistent Segmentation of Longitudinal Brain MR Images with Spatio-Temporal Constrained Networks
  • Context-aware virtual adversarial training for anatomically-plausible segmenation
  • Continuous-Time Deep Glioma Growth Models
  • Controllable cardiac synthesis via disentangled anatomy arithmetic
  • Convolution-Free Medical Image Segmentation using Transformer Networks
  • Cooperative Training and Latent Space Data Augmentation for Robust Medical Image Segmentation
  • CoTr: Efficiently Bridging CNN and Transformer for 3D Medical Image Segmentation
  • CPNet: Cycle Prototype Network for Weakly-supervised 3D Renal Chamber Segmentation
  • DC-Net: Dual Context Network for 2D Medical Image Segmentation
  • Deep Fiber Clustering: Anatomically Informed Unsupervised Deep Learning for Fast and Effective White Matter Parcellation
  • Deep Open Snake Tracker for Vessel Tracing
  • Deep Reinforcement Exemplar Learning for Annotation Refinement
  • Deep-Cleansing: Deep-learning based Electronic Cleansing in Dual-energy CT Colonography
  • DeepMitral: Fully Automatic 3D Echocardiography Segmentation for Patient Specific Mitral Valve Modelling
  • DeepOPG: Improving Orthopantomogram Finding Summarization with Weak Supervision
  • DeepStationing: Thoracic Lymph Node Station Parsing in CT Scans using Anatomical Context Encoding and Key Organ Auto-Search
  • Detecting Hypo-plastic Left Heart Syndrome in Fetal Ultrasound via Disease-specific Atlas Maps
  • Detecting when pre-trained nnU-Net models fail silently for Covid-19 lung lesion segmentation
  • Detection of critical structures in laparoscopic cholecystectomy using label relaxation and self-supervision
  • Distilling effective supervision for robust medical image segmentation with noisy labels
  • Domain Composition and Attention for Unseen-Domain Generalizable Medical Image Segmentation
  • Dual-Consistency Semi-Supervised Learning with Uncertainty Quantification for COVID-19 Lesion Segmentation from CT Images
  • Duo-SegNet: Adversarial Dual-Views for Semi-Supervised Medical Image Segmentation
  • EchoCP: An Echocardiography Dataset in Contrast Transthoracic Echocardiography for Patent Foramen Ovale Diagnosis
  • Effective semantic segmentation in Cataract surgery: What matters most?
  • Efficient and Generic Interactive Segmentation Framework to Correct Mispredictions during Clinical Evaluation of Medical Images
  • Efficient Semi-Supervised Gross Target Volume of Nasopharyngeal Carcinoma Segmentation via Uncertainty Rectified Pyramid Consistency
  • EllipseNet: Anchor-Free Ellipse Detection for Automatic Cardiac Biometrics in Fetal Echocardiography
  • EndoUDA: A modality independent segmentation approach for endoscopy imaging
  • Facial and cochlear nerves characterization using deep reinforcement learning for landmark detection
  • Fairness in Cardiac MR Image Analysis: An Investigation of Bias Due to Data Imbalance in Deep Learning Based Segmentation
  • Federated Contrastive Learning for Volumetric Medical Image Segmentation
  • Federated Whole Prostate Segmentation in MRI with Personalized Neural Architectures
  • Flip Learning: Erase to Segment
  • FoldIt: Haustral Folds Detection and Segmentation in Colonoscopy Videos
  • Fully Test-time Adaptation for Image Segmentation
  • Generalizing Nucleus Recognition Model in Multi-source Ki67 Immunohistochemistry Stained Images via Domain-specific Pruning
  • Group Shift Pointwise Convolution for Volumetric Medical Image Segmentation
  • Hierarchical Self-Supervised Learning for Medical Image Segmentation Based on Multi-Domain Data Aggregation
  • High-resolution segmentation of lumbar vertebrae from conventional thick slice MRI
  • HRENet: A Hard Region Enhancement Network for Polyp Segmentation
  • Hybrid graph convolutional neural networks for anatomical segmentation
  • Implicit field learning for unsupervised anomaly detection in medical images
  • Improved Brain Lesion Segmentation with Anatomical Priors from Healthy Subjects
  • Inter Extreme Points Geodesics for End-to-End Weakly Supervised Image Segmentation
  • Interactive segmentation via deep learning and B-spline explicit active surfaces
  • Joint Motion Correction and Super Resolution for Cardiac Segmentation via Latent Optimisation
  • Joint Segmentation and Quantification of Main Coronary Vessels Using Dual-branch Multi-scale Attention Network
  • kCBAC-Net: Deeply Supervised Complete Bipartite Networks with Asymmetric Convolutions for Medical Image Segmentation
  • Labels-set Loss Functions for Partial Supervision: Application to Fetal Brain 3D MRI Parcellation
  • LambdaUNet: 2.5D Stroke Lesion Segmentation of Diffusion-weighted MR Images
  • Learnable Oriented-Derivative Network for Polyp Segmentation
  • Learning Consistency- and Discrepancy-Context for 2D Organ Segmentation
  • Learning Neuron Stitching for Connectomics
  • Learning to Address Intra-segment Misclassification in Retinal Imaging
  • Learning Whole-Slide Segmentation from Inexact and Incomplete Labels using Tissue Graphs
  • Learning with Noise: Mask-guided Attention Model for Weakly Supervised Nuclei Segmentation
  • LensID: A CNN-RNN-Based Framework Towards Lens Irregularity Detection in Cataract Surgery Videos
  • Lesion Segmentation and RECIST Diameter Prediction via Click-driven Attention and Dual-path Connection
  • LIFE: A Generalizable Autodidactic Pipeline for 3D OCT-A Vessel Segmentation
  • Longitudinal Quantitative Assessment of COVID-19 Infection Progression from Chest CTs
  • MASC-Units: Training Oriented Filters for Segmenting Curvilinear Structures
  • MBFF-Net: Multi-Branch Feature Fusion Network for Carotid Plaque Segmentation in Ultrasound
  • Medical Matting: A New Perspective on Medical Segmentation with Uncertainty
  • Medical Transformer: Gated Axial-Attention for Medical Image Segmentation
  • Modality Completion via Gaussian Process Prior Variational Autoencoders for Multi-Modal Glioma Segmentation
  • Modality-aware Mutual Learning for Multi-modal Medical Image Segmentation
  • MouseGAN: GAN-Based Multiple MRI Modalities Synthesis and Segmentation for Mouse Brain Structures
  • M-SEAM-NAM: Multi-instance Self-supervised Equivalent Attention Mechanism with Neighborhood Affinity Module for Double Weakly Supervised Segmentation of COVID-19
  • MT-UDA: Towards Unsupervised Cross-Modality Medical Image Segmentation with Limited Source Labels
  • Multi-Compound Transformer for Accurate Biomedical Image Segmentation
  • Multi-frame Attention Network for Left Ventricle Segmentation in 3D Echocardiography
  • Multi-phase Liver Tumor Segmentation with Spatial Aggregation and Uncertain Region Inpainting
  • Multi-Task, Multi-Domain Deep Segmentation with Shared Representations and Contrastive Regularization for Sparse Pediatric Datasets
  • Noisy Labels are Treasure: Mean-Teacher-Assisted Confident Learning for Hepatic Vessel Segmentation
  • Nuclei Grading of Clear Cell Renal Cell Carcinoma in Histopathological Image by Composite High-Resolution Network
  • NucMM Dataset: 3D Neuronal Nuclei Instance Segmentation at Sub-Cubic Millimeter Scale
  • OLVA: Optimal Latent Vector Alignment for Unsupervised Domain Adaptation in Medical Image Segmentation
  • On the relationship between calibrated predictors and unbiased volume estimation
  • Orthogonal Ensemble Networks for Biomedical Image Segmentation
  • Pancreas CT Segmentation by Predictive Phenotyping
  • Partial-supervised Learning for Vessel Segmentation in Ocular Images
  • Patch-Free 3D Medical Image Segmentation Driven by Super-Resolution Technique and Self-Supervised Guidance
  • Patient-specific virtual spine straightening and vertebra inpainting: An automatic framework for osteoplasty planning
  • Point-Unet: A Context-aware Point-based Neural Network for Volumetric Segmentation
  • POPCORN: Progressive Pseudo-labeling with Consistency Regularization and Neighboring
  • Positional Contrastive Learning for Volumetric Medical Image Segmentation
  • Progressively Normalized Self-Attention Network for Video Polyp Segmentation
  • Projective Skip-Connections for Segmentation Along a Subset of Dimensions in Retinal OCT
  • Prototypical Interaction Graph for Unsupervised Domain Adaptation in Surgical Instrument Segmentation
  • Quality-Aware Memory Network for Interactive Volumetric Image Segmentation
  • Reciprocal Learning for Semi-supervised Segmentation
  • Refined Local-imbalance-based Weight for Airway Segmentation in CT
  • ReSGAN: Intracranial Hemorrhage Segmentation with Residuals of Synthetic Brain CT Scans
  • Residual Feedback Network for Breast Lesion Segmentation in Ultrasound Image
  • Revisiting contour-driven and knowledge-based deformable models: application to 2D-3D proximal femur reconstruction from X-ray images
  • RibSeg Dataset and Strong Point Cloud Baselines for Rib Segmentation from CT Scans
  • SAR: Scale-Aware Restoration Learning for 3D Tumor Segmentation
  • Scalable joint detection and segmentation of surgical instruments with weak supervision
  • Segmentation of Left Atrial MR Images via Self-supervised Semi-supervised Meta-learning
  • Selective Learning from External Data for CT Image Segmentation
  • Self-Supervised Correction Learning for Semi-Supervised Biomedical Image Segmentation
  • Self-supervised Lesion Change Detection and Localisation in Longitudinal Multiple Sclerosis Brain Imaging
  • Self-Supervised Multi-Modal Alignment For Whole Body Medical Imaging
  • Self-Supervised Vessel Enhancement Using Flow-Based Consistencies
  • Semantic Consistent Unsupervised Domain Adaptation for Cross-modality Medical Image Segmentation
  • Semi-supervised Contrastive Learning for Label-efficient Medical Image Segmentation
  • Semi-supervised Left Atrium Segmentation with Mutual Consistency Training
  • Semi-supervised Meta-learning with Disentanglement for Domain-generalised Medical Image Segmentation
  • Semi-Supervised Unpaired Multi-Modal Learning for Label-Efficient Medical Image Segmentation
  • Sequential Gaussian Process Regression for Simultaneous Pathology Detection and Shape Reconstruction
  • Sequential Learning on Liver Tumor Boundary Semantics and Prognostic Biomarker Mining
  • SGNet: Structure-aware Graph-based Network for Airway Semantic Segmentation
  • Shallow Attention Network for Polyp Segmentation
  • Simultaneous Alignment and Surface Regression Using Hybrid 2D-3D Networks for 3D Coherent Layer Segmentation of Retina OCT Images
  • Sli2Vol: Annotate a 3D Volume from a Single Slice with Self-Supervised Learning
  • Source-Free Domain Adaptive Fundus Image Segmentation with Denoised Pseudo-Labeling
  • Stain Mix-up: Unsupervised Domain Generalization for Histopathology Images
  • Study Group Learning: Improving Retinal Vessel Segmentation Trained with Noisy Labels
  • Style Curriculum Learning for Robust Medical Image Segmentation
  • Superpixel-guided Iterative Learning from Noisy Labels for Medical Image Segmentation
  • Symmetry-Enhanced Attention Network for Acute Ischemic Infarct Segmentation with Non–Contrast CT Images
  • TarGAN: Target-Aware Generative Adversarial Networks for Multi-modality Medical Image Translation
  • TEDS-Net: Enforcing Diffeomorphisms in Spatial Transformers to Guarantee Topology Preservation in Segmentations
  • Towards Efficient Human-Machine Collaboration: Real-Time Correction Effort Prediction for Ultrasound Data Acquisition
  • Towards Robust General Medical Image Segmentation
  • TransBTS: Multimodal Brain Tumor Segmentation Using Transformer
  • TransFuse: Fusing Transformers and CNNs for Medical Image Segmentation
  • Tripled-uncertainty Guided Mean Teacher model for Semi-supervised Medical Image Segmentation
  • TumorCP: A Simple but Effective Object-Level Data Augmentation for Tumor Segmentation
  • TUN-Det: A Novel Network for Thyroid Ultrasound Nodule Detection
  • Uncertainty-Aware Label Rectification for Domain Adaptive Mitochondria Segmentation
  • Unsupervised Domain Adaptation for Small Bowel Segmentation using Disentangled Representation
  • Unsupervised Network Learning for Cell Segmentation
  • USCL: Pretraining Deep Ultrasound Image Diagnosis Model through Video Contrastive Representation Learning
  • UTNet: A Hybrid Transformer Architecture for Medical Image Segmentation
  • Weakly supervised pan-cancer segmentation tool
  • Weakly-Supervised Universal Lesion Segmentation with Regional Level Set Loss
  • Whole Heart Mesh Generation For Image-Based Computational Simulations By Learning Free-From Deformations

    • Image-Guided Interventions and Surgery

  • 2.5D Thermometry Maps for MRI-guided Tumor Ablation
  • 3D Brain Midline Delineation for Hematoma Patients
  • Adversarial Domain Feature Adaptation for Bronchoscopic Depth Estimation
  • Automatic Path Planning for Safe Guide Pin Insertion in PCL Reconstruction Surgery
  • C-arm positioning for spinal standard projections in different intra-operative settings
  • CataNet: Predicting remaining cataract surgery duration
  • Class-Incremental Domain Adaptation with Smoothing and Calibration for Surgical Report Generation
  • Co-Generation and Segmentation for Generalized Surgical Instrument Segmentation on Unlabelled Data
  • CPNet: Cycle Prototype Network for Weakly-supervised 3D Renal Chamber Segmentation
  • Deep Iterative 2D/3D Registration
  • DeepMitral: Fully Automatic 3D Echocardiography Segmentation for Patient Specific Mitral Valve Modelling
  • Detection of critical structures in laparoscopic cholecystectomy using label relaxation and self-supervision
  • Determination of error in 3D CT to 2D fluoroscopy image registration for endobronchial guidance
  • Distortion Energy for Deep Learning-based Volumetric Finite Element Mesh Generation for Aortic Valves
  • E-DSSR: Efficient Dynamic Surgical Scene Reconstruction with Transformer-based Stereoscopic Depth Perception
  • Effective semantic segmentation in Cataract surgery: What matters most?
  • Efficient Global-Local Memory for Real-time Instrument Segmentation of Robotic Surgical Video
  • EMDQ-SLAM: Real-time High-resolution Reconstruction of Soft Tissue Surface from Stereo Laparoscopy Videos
  • Explainable Classification of Weakly Annotated Wireless Capsule Endoscopy Images based on a Fuzzy Bag-of-Colour Features Model and Brain Storm Optimization
  • Facial and cochlear nerves characterization using deep reinforcement learning for landmark detection
  • hSDB-instrument: Instrument Localization Database for Laparoscopic and Robotic Surgeries
  • Image-based Incision Detection for Topological Intraoperative 3D Model Update in Augmented Reality Assisted Laparoscopic Surgery
  • Image-to-Graph Convolutional Network for Deformable Shape Reconstruction from a Single Projection Image
  • Intra-operative Update of Boundary Conditions for Patient-specific Surgical Simulation
  • LDPolypVideo Benchmark: A Large-scale Colonoscopy Video Dataset of Diverse Polyps
  • Multimodal Sensing Guidewire for C-arm Navigation with Random UV Enhanced Optical Sensors using Spatio-temporal Networks
  • Multi-View Surgical Video Action Detection via Mixed Global View Attention
  • Personalized Respiratory Motion Model Using Conditional Generative Networks for MR-Guided Radiotherapy
  • Prototypical Interaction Graph for Unsupervised Domain Adaptation in Surgical Instrument Segmentation
  • Quantitative Assessments for Ultrasound Probe Calibration
  • Real-Time Rotated Convolutional Descriptor for Surgical Environments
  • Residual Feedback Network for Breast Lesion Segmentation in Ultrasound Image
  • Revisiting contour-driven and knowledge-based deformable models: application to 2D-3D proximal femur reconstruction from X-ray images
  • Scalable joint detection and segmentation of surgical instruments with weak supervision
  • Self-Supervised Generative Adversarial Network for Depth Estimation in Laparoscopic Images
  • SpineGEM: A Hybrid-Supervised Model Generation Strategy Enabling Accurate Spine Disease Classification with a Small Training Dataset
  • SurgeonAssist-Net: Towards Context-Aware Head-Mounted Display-Based Augmented Reality for Surgical Guidance
  • Surgical Instruction Generation with Transformers
  • Task Fingerprinting for Meta Learning in Biomedical Image Analysis
  • Using Multiple Images and Contours for Deformable 3D-2D Registration of a Preoperative CT in Laparoscopic Liver Surgery
  • Whole Heart Mesh Generation For Image-Based Computational Simulations By Learning Free-From Deformations

    • Integration of Imaging with Non-Imaging Biomarkers

  • A Matrix Auto-encoder Framework to Align the Functional and Structural Connectivity Manifolds as Guided by Behavioral Phenotypes
  • A Novel Bayesian Semi-parametric Model for Learning Heritable Imaging Traits
  • Co-Graph Attention Reasoning based Imaging and Clinical Features Integration for Lymph Node Metastasis Prediction
  • Combining 3D Image and Tabular Data via the Dynamic Affine Feature Map Transform
  • Deep Orthogonal Fusion: Multimodal Prognostic Biomarker Discovery Integrating Radiology, Pathology, Genomic, and Clinical Data
  • GKD: Semi-supervised Graph Knowledge Distillation for Graph-Independent Inference
  • Hierarchical graph pathomic network for progression free survival prediction
  • Image-derived phenotype extraction for genetic discovery via unsupervised deep learning in CMR images
  • Intracerebral Haemorrhage Growth Prediction Based on Displacement Vector Field and Clinical Metadata
  • Lung Cancer Risk Estimation with Incomplete Data: A Joint Missing Imputation Perspective
  • Multi-modal Multi-instance Learning using Weakly Correlated Histopathological Images and Tabular Clinical Information
  • Pancreas CT Segmentation by Predictive Phenotyping
  • Predicting Esophageal Fistula Risks Using a Multimodal Self-Attention Network
  • Recurrent Multigraph Integrator Network for Predicting the Evolution of Population-Driven Brain Connectivity Templates

    • Interventional Imaging Systems

  • C-arm positioning for spinal standard projections in different intra-operative settings
  • Estimation of High Frame Rate Digital Subtraction Angiography Sequences at Low Radiation Dose
  • hSDB-instrument: Instrument Localization Database for Laparoscopic and Robotic Surgeries
  • Multimodal Sensing Guidewire for C-arm Navigation with Random UV Enhanced Optical Sensors using Spatio-temporal Networks
  • Personalized Respiratory Motion Model Using Conditional Generative Networks for MR-Guided Radiotherapy

    • Interventional Simulation Systems

  • Improving hexahedral-FEM-based plasticity in surgery simulation
  • Rapid treatment planning for low-dose-rate prostate brachytherapy with TP-GAN
  • Whole Heart Mesh Generation For Image-Based Computational Simulations By Learning Free-From Deformations

    • Machine Learning - Active Learning

  • Annotation-efficient Cell Counting
  • Conditional GAN with an Attention-based Generator and a 3D Discriminator for 3D Medical Image Generation
  • Partial-supervised Learning for Vessel Segmentation in Ocular Images
  • Targeted Gradient Descent: A Novel Method for Convolutional Neural Networks Fine-tuning and Online-learning

    • Machine Learning - Attention models

  • A Multi-attribute Controllable Generative Model for Histopathology Image Synthesis
  • A Topological-Attention ConvLSTM Network and Its Application to EM Images
  • Accounting for Dependencies in Deep Learning based Multiple Instance Learning for Whole Slide Imaging
  • Automated Malaria Cells Detection from Blood Smears under Severe Class Imbalance via Importance-aware Balanced Group Softmax
  • CarveMix: A Simple Data Augmentation Method for Brain Lesion Segmentation
  • Combining Attention-based Multiple Instance Learning and Gaussian Processes for CT Hemorrhage Detection
  • Conditional GAN with an Attention-based Generator and a 3D Discriminator for 3D Medical Image Generation
  • Continuous-Time Deep Glioma Growth Models
  • Convolution-Free Medical Image Segmentation using Transformer Networks
  • Cross-modal Attention for MRI and Ultrasound Volume Registration
  • Deep Iterative 2D/3D Registration
  • DLLNet: An Attention-based Deep Learning Method for Dental Landmark Localization on High-Resolution 3D Digital Dental Models
  • Domain Composition and Attention for Unseen-Domain Generalizable Medical Image Segmentation
  • Group Shift Pointwise Convolution for Volumetric Medical Image Segmentation
  • Hierarchical Attention Guided Framework for Multi-resolution Collaborative Whole Slide Image Segmentation
  • Hierarchical graph pathomic network for progression free survival prediction
  • Improving Pneumonia Localization via Cross-Attention on Medical Images and Reports
  • Instance-based Vision Transformer for Subtyping of Papillary Renal Cell Carcinoma in Histopathological Image
  • Integration of Patch Features through Self-Supervised Learning and Transformer for Survival Analysis on Whole Slide Images
  • Learning Dual Transformer Network for Diffeomorphic Registration
  • LensID: A CNN-RNN-Based Framework Towards Lens Irregularity Detection in Cataract Surgery Videos
  • Medical Transformer: Gated Axial-Attention for Medical Image Segmentation
  • mfTrans-Net: Quantitative Measurement of Hepatocellular Carcinoma via Multi-Function Transformer Regression Network
  • MIL-VT: Multiple Instance Learning Enhanced Vision Transformer for Fundus Image Classification
  • MorphSet: Improving Renal Histopathology Case Assessment Through Learned Prognostic Vectors
  • Multi-frame Collaboration for Effective Endoscopic Video Polyp Detection via Spatial-Temporal Feature Transformation
  • Multi-Head GAGNN: A Multi-Head Guided Attention Graph Neural Network for Modeling Spatio-Temporal Patterns of Holistic Brain Functional Networks
  • Multiple Instance Learning with Auxiliary Task Weighting for Multiple Myeloma Classification
  • Multi-view analysis of unregistered medical images using cross-view transformers
  • Multi-View Surgical Video Action Detection via Mixed Global View Attention
  • OperA: Attention-Regularized Transformers for Surgical Phase Recognition
  • OXnet: Deep Omni-supervised Thoracic Disease Detection from Chest X-rays
  • Pay Attention with Focus: A Novel Learning Scheme for Classification of Whole Slide Images
  • Predicting Esophageal Fistula Risks Using a Multimodal Self-Attention Network
  • Predicting Symptoms from Multiphasic MRI via Multi-Instance Attention Learning for Hepatocellular Carcinoma Grading
  • Self-adversarial Learning for Detection of Clustered Microcalcifications in Mammograms
  • Spine-Transformers: Vertebra Detection and Localization in Arbitrary Field-of-View Spine CT with Transformers
  • Surgical Instruction Generation with Transformers
  • Symmetry-Enhanced Attention Network for Acute Ischemic Infarct Segmentation with Non–Contrast CT Images
  • Text2Brain: Synthesis of Brain Activation Maps from Free-form Text Query
  • Trainable summarization to improve breast tomosynthesis classification
  • Transformer Network for Significant Stenosis Detection in CCTA of Coronary Arteries
  • TransFuse: Fusing Transformers and CNNs for Medical Image Segmentation
  • Trans-SVNet: Accurate Phase Recognition from Surgical Videos via Hybrid Embedding Aggregation Transformer
  • Ultrasound Video Transformers for Cardiac Ejection Fraction Estimation
  • Uncertainty-Guided Progressive GANs for Medical Image Translation
  • UTNet: A Hybrid Transformer Architecture for Medical Image Segmentation
  • Variational Topic Inference for Chest X-Ray Report Generation
  • Whole Slide Images are 2D Point Clouds: Context-Aware Survival Prediction using Patch-based Graph Convolutional Networks

    • Machine Learning - Domain adaptation

  • 3D Semantic Mapping from Arthroscopy using Out-of-distribution Pose and Depth and In-distribution Segmentation Training
  • A Coherent Cooperative Learning Framework Based on Transfer Learning for Unsupervised Cross-domain Classification
  • A Unified Hyper-GAN Model for Unpaired Multi-contrast MR Image Translation
  • ACN: Adversarial Co-training Network for Brain Tumor Segmentation with Missing Modalities
  • Adversarial Domain Feature Adaptation for Bronchoscopic Depth Estimation
  • Anatomy of Domain Shift Impact on U-Net Layers in MRI Segmentation
  • Anatomy-Constrained Contrastive Learning for Synthetic Segmentation without Ground-truth
  • Cell Detection in Domain Shift Problem Using Pseudo-Cell-Position Heatmap
  • Class-Incremental Domain Adaptation with Smoothing and Calibration for Surgical Report Generation
  • Colorectal Polyp Classification from White-light Colonoscopy Images via Domain Alignment
  • Comprehensive Importance-based Selective Regularization for Continual Segmentation Across Multiple Sites
  • Conditional GAN with an Attention-based Generator and a 3D Discriminator for 3D Medical Image Generation
  • Controllable cardiac synthesis via disentangled anatomy arithmetic
  • Cost-Sensitive Meta-Learning for Progress Prediction of Subjective Cognitive Decline with Brain Structural MRI
  • Culprit-Prune-Net: Efficient Continual Sequential Multi-Domain Learning with Application to Skin Lesion Classification
  • Data-driven mapping between functional connectomes using optimal transport
  • Deep J-Sense: Accelerated MRI Reconstruction via Unrolled Alternating Optimization
  • Domain Composition and Attention for Unseen-Domain Generalizable Medical Image Segmentation
  • Domain Generalization for Mammography Detection via Multi-style and Multi-view Contrastive Learning
  • EndoUDA: A modality independent segmentation approach for endoscopy imaging
  • Federated Whole Prostate Segmentation in MRI with Personalized Neural Architectures
  • Few-Shot Domain Adaptation with Polymorphic Transformers
  • FoldIt: Haustral Folds Detection and Segmentation in Colonoscopy Videos
  • Fully Test-time Adaptation for Image Segmentation
  • Functional Magnetic Resonance Imaging data augmentation through conditional ICA
  • Generalizing Nucleus Recognition Model in Multi-source Ki67 Immunohistochemistry Stained Images via Domain-specific Pruning
  • Generative Self-training for Cross-domain Unsupervised Tagged-to-Cine MRI Synthesis
  • Harmonization with Flow-based Causal Inference
  • High-Resolution Hierarchical Adversarial Learning for OCT Speckle Noise Reduction
  • hSDB-instrument: Instrument Localization Database for Laparoscopic and Robotic Surgeries
  • Instance-aware Feature Alignment for Cross-domain Cell Nuclei Detection in Histopathology Images
  • MetaCon: Meta Contrastive Learning for Microsatellite Instability Detection
  • MT-UDA: Towards Unsupervised Cross-Modality Medical Image Segmentation with Limited Source Labels
  • Multiple Meta-model Quantifying for Medical Visual Question Answering
  • Multi-site Incremental Image Quality Assessment of Structural MRI via Consensus Adversarial Representation Adaptation
  • Multi-Task, Multi-Domain Deep Segmentation with Shared Representations and Contrastive Regularization for Sparse Pediatric Datasets
  • OLVA: Optimal Latent Vector Alignment for Unsupervised Domain Adaptation in Medical Image Segmentation
  • Phase-independent Latent Representation for Cardiac Shape Analysis
  • Predicting Symptoms from Multiphasic MRI via Multi-Instance Attention Learning for Hepatocellular Carcinoma Grading
  • Primary Tumor and Inter-Organ Augmentations for Supervised Lymph Node Colon Adenocarcinoma Metastasis Detection
  • Pristine annotations-based multi-modal trained artificial intelligence solution to triage chest X-Ray for COVID19
  • Prototypical Interaction Graph for Unsupervised Domain Adaptation in Surgical Instrument Segmentation
  • Q-space Conditioned Translation Networks for Directional Synthesis of Diffusion Weighted Images from Multi-modal Structural MRI
  • Reference-Relation Guided Autoencoder with Deep CCA Restriction for Awake-to-Sleep Brain Functional Connectome Prediction
  • Semantic Consistent Unsupervised Domain Adaptation for Cross-modality Medical Image Segmentation
  • Semi-supervised Meta-learning with Disentanglement for Domain-generalised Medical Image Segmentation
  • Source-Free Domain Adaptive Fundus Image Segmentation with Denoised Pseudo-Labeling
  • Stain Mix-up: Unsupervised Domain Generalization for Histopathology Images
  • Structure-Preserving Multi-Domain Stain Color Augmentation using Style-Transfer with Disentangled Representations
  • Style Transfer Using Generative Adversarial Networks for Multi-Site MRI Harmonization
  • SyNCCT: Synthetic Non-Contrast Images of the Brain from Single-Energy Computed Tomography Angiography
  • Synthesis of Contrast-enhanced Spectral Mammograms from Low-energy Mammograms Using cGAN-Based Synthesis Network
  • Synthesizing Multi-Tracer PET Images for Alzheimer's Disease Patients using a 3D Unified Anatomy-aware Cyclic Adversarial Network
  • Targeted Gradient Descent: A Novel Method for Convolutional Neural Networks Fine-tuning and Online-learning
  • Task Fingerprinting for Meta Learning in Biomedical Image Analysis
  • Uncertainty-Aware Label Rectification for Domain Adaptive Mitochondria Segmentation
  • Unsupervised Domain Adaptation for Small Bowel Segmentation using Disentangled Representation
  • USCL: Pretraining Deep Ultrasound Image Diagnosis Model through Video Contrastive Representation Learning
  • You Only Learn Once: Universal Anatomical Landmark Detection

    • Machine Learning - Interpretability / Explainability

  • 3D-UCaps: 3D Capsules Unet for Volumetric Image Segmentation
  • A Location Constrained Dual-branch Network for Reliable Diagnosis of Jaw Tumors and Cysts
  • A Matrix Auto-encoder Framework to Align the Functional and Structural Connectivity Manifolds as Guided by Behavioral Phenotypes
  • A Multi-attribute Controllable Generative Model for Histopathology Image Synthesis
  • A Principled Approach to Failure Analysis and Model Repairment: Demonstration in Medical Imaging
  • A spherical convolutional neural network for white matter structure imaging via diffusion MRI
  • Accounting for Dependencies in Deep Learning based Multiple Instance Learning for Whole Slide Imaging
  • Adversarial learning of cancer tissue representations
  • An Interpretable Approach to Automated Severity Scoring in Pelvic Trauma
  • BSDA-Net: A Boundary Shape and Distance Aware Joint Learning Framework for Segmenting and Classifying OCTA Images
  • Conditional GAN with an Attention-based Generator and a 3D Discriminator for 3D Medical Image Generation
  • Controllable cardiac synthesis via disentangled anatomy arithmetic
  • Deep Neural Dynamic Bayesian Networks applied to EEG sleep spindles modeling
  • Demystifying T1-MRI to FDG18-PET Image Translation via Representational Similarity
  • Detecting Hypo-plastic Left Heart Syndrome in Fetal Ultrasound via Disease-specific Atlas Maps
  • Disentangled Sequential Graph Autoencoder for Preclinical Alzheimer's Disease Characterizations from ADNI Study
  • Explainable Classification of Weakly Annotated Wireless Capsule Endoscopy Images based on a Fuzzy Bag-of-Colour Features Model and Brain Storm Optimization
  • Explaining COVID-19 and Thoracic Pathology Model Predictions by Identifying Informative Input Features
  • Exploring the Functional Difference of Gyri/Sulci via Hierarchical Interpretable Autoencoder
  • Fighting Class Imbalance with Contrastive Learning
  • Graph Transformers for Characterization and Interpretation of Surgical Margins
  • Improving the Explainability of Skin Cancer Diagnosis Using CBIR
  • Integration of Patch Features through Self-Supervised Learning and Transformer for Survival Analysis on Whole Slide Images
  • Interpretable deep learning for multimodal super-resolution of medical images
  • Interpretable gender classification from retinal fundus images using BagNets
  • Learning More for Free - A Multi Task Learning Approach for Improved Pathology Classification in Capsule Endoscopy
  • Linear Prediction Residual for Efficient Diagnosis of Parkinson's Disease from Gait
  • Local-global Dual Perception based Deep Multiple Instance Learning for Retinal Disease Classification
  • Longitudinal self-supervision to disentangle inter-patient variability from disease progression
  • PAC Bayesian Performance Guarantees for (Stochastic) Deep Networks in Medical Imaging
  • Personalized CT Organ Dose Estimation from Scout Images
  • Phase-independent Latent Representation for Cardiac Shape Analysis
  • Point-Unet: A Context-aware Point-based Neural Network for Volumetric Segmentation
  • Predicting Symptoms from Multiphasic MRI via Multi-Instance Attention Learning for Hepatocellular Carcinoma Grading
  • Projection-wise Disentangling for Fair and Interpretable Representation Learning: Application to 3D Facial Shape Analysis
  • RATCHET: Medical Transformer for Chest X-ray Diagnosis and Reporting
  • Scalable, Axiomatic Explanations of Deep Alzheimer's Diagnosis from Heterogeneous Data
  • Seg4Reg+: A Local and Global ConsistencyLearning between Spine Segmentation and CobbAngle Regression
  • Self-supervised visual representation learning for histopathological images
  • Sharpening Local Interpretable Model-agnostic Explanations for Histopathology: Improved Understandability and Reliability
  • SPARTA: An Integrated Stability, Discriminability, and Sparsity based Radiomic Feature Selection Approach
  • SurgeonAssist-Net: Towards Context-Aware Head-Mounted Display-Based Augmented Reality for Surgical Guidance
  • Task-Oriented Low-Dose CT Image Denoising
  • The Power of Proxy Data and Proxy Networks for Hyper-Parameter Optimization for Medical Image Segmentation
  • Towards Robust General Medical Image Segmentation
  • Towards Semantic Interpretation of Thoracic Disease and COVID-19 Diagnosis Models
  • Uncertainty-Guided Progressive GANs for Medical Image Translation
  • Using Causal Analysis for Conceptual Deep Learning Explanation
  • VinDr-SpineXR: A deep learning framework for spinal lesions detection and classification from radiographs
  • Whole Slide Images are 2D Point Clouds: Context-Aware Survival Prediction using Patch-based Graph Convolutional Networks

    • Machine Learning - Reinforcement learning

  • A Deep Reinforced Tree-traversal Agent for Coronary Artery Centerline Extraction
  • A new Approach to Orthopedic Surgery Planning using Deep Reinforcement Learning and Simulation
  • Context-aware virtual adversarial training for anatomically-plausible segmenation
  • Deep Reinforcement Exemplar Learning for Annotation Refinement
  • DeepOPG: Improving Orthopantomogram Finding Summarization with Weak Supervision
  • Facial and cochlear nerves characterization using deep reinforcement learning for landmark detection
  • Flip Learning: Erase to Segment
  • SPARTA: An Integrated Stability, Discriminability, and Sparsity based Radiomic Feature Selection Approach
  • Surgical Instruction Generation with Transformers
  • Uncertainty Aware Deep Reinforcement Learning for Anatomical Landmark Detection in Medical Images

    • Machine Learning - Self-supervised learning

  • A Multi-attribute Controllable Generative Model for Histopathology Image Synthesis
  • A self-supervised deep framework for reference bony shape estimation in orthognathic surgical planning
  • A Spatial Guided Self-supervised Clustering Network for Medical Image Segmentation
  • Anatomy-Constrained Contrastive Learning for Synthetic Segmentation without Ground-truth
  • Chest Radiograph Disentanglement for COVID-19 Outcome Prediction
  • Conditional GAN with an Attention-based Generator and a 3D Discriminator for 3D Medical Image Generation
  • Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images
  • Contrastive Learning Based Stain Normalization Across Multiple Tumor Histopathology
  • Contrastive Learning of Relative Position Regression for One-Shot Object Localization in 3D Medical Images
  • Contrastive Learning with Continuous Proxy Meta-Data For 3D MRI Classification
  • Contrastive Pre-training and Representation Distillation for Medical Visual Question Answering Based on Radiology Images
  • Cooperative Training and Latent Space Data Augmentation for Robust Medical Image Segmentation
  • Deep Fiber Clustering: Anatomically Informed Unsupervised Deep Learning for Fast and Effective White Matter Parcellation
  • Deformed2Self: Self-Supervised Denoising for Dynamic Medical Imaging
  • Depth Estimation for Colonoscopy Images with Self-supervised Learning from Videos
  • Detecting Outliers with Poisson Image Interpolation
  • Detection of critical structures in laparoscopic cholecystectomy using label relaxation and self-supervision
  • Distilling effective supervision for robust medical image segmentation with noisy labels
  • Domain Generalization for Mammography Detection via Multi-style and Multi-view Contrastive Learning
  • Efficient neural network approximation of robust PCA for automated analysis of calcium imaging data
  • Federated Contrastive Learning for Decentralized Unlabeled Medical Images
  • Federated Contrastive Learning for Volumetric Medical Image Segmentation
  • From Brain to Body: Learning Low-Frequency Respiration and Cardiac Signals from fMRI Dynamics
  • Generalised Super Resolution for Quantitative MRI Using Self-Supervised Mixture of Experts
  • Hierarchical graph pathomic network for progression free survival prediction
  • Hierarchical Self-Supervised Learning for Medical Image Segmentation Based on Multi-Domain Data Aggregation
  • Imbalance-Aware Self-Supervised Learning for 3D Radiomic Representations
  • Implicit field learning for unsupervised anomaly detection in medical images
  • Implicit Neural Distance Representation for Unsupervised and Supervised Classification of Complex Anatomies
  • Integration of Patch Features through Self-Supervised Learning and Transformer for Survival Analysis on Whole Slide Images
  • Inter-Regional High-level Relation Learning from Functional Connectivity via Self-Supervision
  • IREM: High-Resolution Magnetic Resonance Image Reconstruction via Implicit Neural Representation
  • Joint Motion Correction and Super Resolution for Cardiac Segmentation via Latent Optimisation
  • Learning 4D Infant Cortical Surface Atlas with Unsupervised Spherical Networks
  • Learning More for Free - A Multi Task Learning Approach for Improved Pathology Classification in Capsule Endoscopy
  • Learning Unsupervised Parameter-specific Affine Transformation for Medical Images Registration
  • Learning Visual Features by Colorization for Slide-Consistent Survival Prediction from Whole Slide Images
  • Lesion-based Contrastive Learning for Diabetic Retinopathy Grading from Fundus Images
  • LIFE: A Generalizable Autodidactic Pipeline for 3D OCT-A Vessel Segmentation
  • Longitudinal Correlation Analysis for Decoding Multi-Modal Brain Development
  • Longitudinal self-supervision to disentangle inter-patient variability from disease progression
  • M-SEAM-NAM: Multi-instance Self-supervised Equivalent Attention Mechanism with Neighborhood Affinity Module for Double Weakly Supervised Segmentation of COVID-19
  • Multimodal Representation Learning via Maximization of Local Mutual Information
  • Multi-scale Neural ODEs for 3D Medical Image Registration
  • One-Shot Medical Landmark Detection
  • Patch-Free 3D Medical Image Segmentation Driven by Super-Resolution Technique and Self-Supervised Guidance
  • Personalized CT Organ Dose Estimation from Scout Images
  • Personalized Respiratory Motion Model Using Conditional Generative Networks for MR-Guided Radiotherapy
  • Positional Contrastive Learning for Volumetric Medical Image Segmentation
  • Residual Feedback Network for Breast Lesion Segmentation in Ultrasound Image
  • SAME: Deformable Image Registration based on Self-supervised Anatomical Embeddings
  • SAR: Scale-Aware Restoration Learning for 3D Tumor Segmentation
  • Segmentation of Left Atrial MR Images via Self-supervised Semi-supervised Meta-learning
  • Self Context and Shape Prior for Sensorless Freehand 3D Ultrasound Reconstruction
  • Self-Supervised Correction Learning for Semi-Supervised Biomedical Image Segmentation
  • Self-Supervised Generative Adversarial Network for Depth Estimation in Laparoscopic Images
  • Self-Supervised Learning for MRI Reconstruction with a Parallel Network Training Framework
  • Self-supervised Lesion Change Detection and Localisation in Longitudinal Multiple Sclerosis Brain Imaging
  • Self-Supervised Longitudinal Neighbourhood Embedding
  • Self-Supervised Multi-Modal Alignment For Whole Body Medical Imaging
  • Self-Supervised Vessel Enhancement Using Flow-Based Consistencies
  • Self-supervised visual representation learning for histopathological images
  • Sequential Gaussian Process Regression for Simultaneous Pathology Detection and Shape Reconstruction
  • SimTriplet: Simple Triplet Representation Learning with a Single GPU
  • Sli2Vol: Annotate a 3D Volume from a Single Slice with Self-Supervised Learning
  • SpineGEM: A Hybrid-Supervised Model Generation Strategy Enabling Accurate Spine Disease Classification with a Small Training Dataset
  • SSLP: Spatial Guided Self-supervised Learning on Pathological Images
  • STRESS: Super-Resolution for Dynamic Fetal MRI using Self-Supervised Learning
  • Topological Learning and Its Application to Multimodal Brain Network Integration
  • Training Automatic View Planner for Cardiac MR Imaging via Self-Supervision by Spatial Relationship between Views
  • Two-Stage Self-Supervised Cycle-Consistency Network for Reconstruction of Thin-Slice MR Images
  • Unsupervised Contrastive Learning of Radiomics and Deep Features for Label-Efficient Tumor Classification
  • Unsupervised Diffeomorphic Surface Registration and Non-Linear Modelling
  • Unsupervised Representation Learning Meets Pseudo-Label Supervised Self-Distillation: A New Approach to Rare Disease Classification

    • Machine Learning - Semi-supervised learning

  • 3D Graph-S2Net: Shape-Aware Self-Ensembling Network for Semi-Supervised Segmentation with Bilateral Graph Convolution
  • 3D Semantic Mapping from Arthroscopy using Out-of-distribution Pose and Depth and In-distribution Segmentation Training
  • A Deep Network for Joint Registration and Parcellation of Cortical Surfaces
  • Anatomy-Constrained Contrastive Learning for Synthetic Segmentation without Ground-truth
  • Annotation-efficient Cell Counting
  • Cell Detection from Imperfect Annotation by Pseudo Label Selection Using P-classification
  • Cell Detection in Domain Shift Problem Using Pseudo-Cell-Position Heatmap
  • Conditional GAN with an Attention-based Generator and a 3D Discriminator for 3D Medical Image Generation
  • Context-aware virtual adversarial training for anatomically-plausible segmenation
  • Detection of critical structures in laparoscopic cholecystectomy using label relaxation and self-supervision
  • Disentangled Sequential Graph Autoencoder for Preclinical Alzheimer's Disease Characterizations from ADNI Study
  • Dual-Consistency Semi-Supervised Learning with Uncertainty Quantification for COVID-19 Lesion Segmentation from CT Images
  • Duo-SegNet: Adversarial Dual-Views for Semi-Supervised Medical Image Segmentation
  • Efficient Semi-Supervised Gross Target Volume of Nasopharyngeal Carcinoma Segmentation via Uncertainty Rectified Pyramid Consistency
  • Federated Contrastive Learning for Volumetric Medical Image Segmentation
  • Federated Semi-supervised Medical Image Classification via Inter-client Relation Matching
  • FedPerl: Semi-Supervised Peer Learning for Skin Lesion Classification
  • Few Trust Data Guided Annotation Refinement for Upper Gastrointestinal Anatomy Recognition
  • Few-Shot Domain Adaptation with Polymorphic Transformers
  • Functional Magnetic Resonance Imaging data augmentation through conditional ICA
  • GKD: Semi-supervised Graph Knowledge Distillation for Graph-Independent Inference
  • I-SECRET: Importance-guided fundus image enhancement via semi-supervised contrastive constraining
  • Joint PVL Detection and Manual Ability Classification using Semi-Supervised Multi-task Learning
  • MT-UDA: Towards Unsupervised Cross-Modality Medical Image Segmentation with Limited Source Labels
  • Multimodal Representation Learning via Maximization of Local Mutual Information
  • Neighbor Matching for Semi-supervised Learning
  • One-Shot Medical Landmark Detection
  • Order-Guided Disentangled Representation Learning for Ulcerative Colitis Classification with Limited Labels
  • OXnet: Deep Omni-supervised Thoracic Disease Detection from Chest X-rays
  • Partial-supervised Learning for Vessel Segmentation in Ocular Images
  • Pay Attention with Focus: A Novel Learning Scheme for Classification of Whole Slide Images
  • POPCORN: Progressive Pseudo-labeling with Consistency Regularization and Neighboring
  • Positional Contrastive Learning for Volumetric Medical Image Segmentation
  • Projection-wise Disentangling for Fair and Interpretable Representation Learning: Application to 3D Facial Shape Analysis
  • Reciprocal Learning for Semi-supervised Segmentation
  • Scalable joint detection and segmentation of surgical instruments with weak supervision
  • Segmentation of Left Atrial MR Images via Self-supervised Semi-supervised Meta-learning
  • Self-Supervised Correction Learning for Semi-Supervised Biomedical Image Segmentation
  • Self-supervised visual representation learning for histopathological images
  • Semi-supervised Adversarial Learning for Stain Normalisation in Histopathology Images
  • Semi-supervised Cell Detection in Time-lapse Images Using Temporal Consistency
  • Semi-supervised Contrastive Learning for Label-efficient Medical Image Segmentation
  • Semi-Supervised Learning for Bone Mineral Density Estimation in Hip X-ray Images
  • Semi-supervised Left Atrium Segmentation with Mutual Consistency Training
  • Semi-supervised Meta-learning with Disentanglement for Domain-generalised Medical Image Segmentation
  • Semi-Supervised Unpaired Multi-Modal Learning for Label-Efficient Medical Image Segmentation
  • Spectral Embedding Approximation and Descriptor Learning for Craniofacial Volumetric Image Correspondence
  • Tripled-uncertainty Guided Mean Teacher model for Semi-supervised Medical Image Segmentation
  • USCL: Pretraining Deep Ultrasound Image Diagnosis Model through Video Contrastive Representation Learning

    • Machine Learning - Uncertainty

  • Airway Anomaly Detection by Graph Neural Network
  • Combining Attention-based Multiple Instance Learning and Gaussian Processes for CT Hemorrhage Detection
  • Comprehensive Importance-based Selective Regularization for Continual Segmentation Across Multiple Sites
  • Continuous-Time Deep Glioma Growth Models
  • Deep Neural Dynamic Bayesian Networks applied to EEG sleep spindles modeling
  • Detecting when pre-trained nnU-Net models fail silently for Covid-19 lung lesion segmentation
  • Efficient Semi-Supervised Gross Target Volume of Nasopharyngeal Carcinoma Segmentation via Uncertainty Rectified Pyramid Consistency
  • EMA: Auditing Data Removal from Trained Models
  • Explainable Classification of Weakly Annotated Wireless Capsule Endoscopy Images based on a Fuzzy Bag-of-Colour Features Model and Brain Storm Optimization
  • Learning to Predict Error for MRI Reconstruction
  • Medical Matting: A New Perspective on Medical Segmentation with Uncertainty
  • Multi-phase Liver Tumor Segmentation with Spatial Aggregation and Uncertain Region Inpainting
  • On the relationship between calibrated predictors and unbiased volume estimation
  • Orthogonal Ensemble Networks for Biomedical Image Segmentation
  • PAC Bayesian Performance Guarantees for (Stochastic) Deep Networks in Medical Imaging
  • Predicting Symptoms from Multiphasic MRI via Multi-Instance Attention Learning for Hepatocellular Carcinoma Grading
  • Semi-supervised Left Atrium Segmentation with Mutual Consistency Training
  • Sequential Gaussian Process Regression for Simultaneous Pathology Detection and Shape Reconstruction
  • Towards Ultrafast MRI via Extreme k-Space Undersampling and Superresolution
  • Uncertainty Aware Deep Reinforcement Learning for Anatomical Landmark Detection in Medical Images
  • Uncertainty-Guided Progressive GANs for Medical Image Translation
  • Variational Topic Inference for Chest X-Ray Report Generation

    • Machine Learning - Weakly supervised learning

  • A Deep Discontinuity-Preserving Image Registration Network
  • Accounting for Dependencies in Deep Learning based Multiple Instance Learning for Whole Slide Imaging
  • Adapting Off-the-Shelf Source Segmenter for Target Medical Image Segmentation
  • Airway Anomaly Detection by Graph Neural Network
  • AMINN: Autoencoder-based Multiple Instance Neural Network Improves Outcome Prediction of Multifocal Liver Metastases
  • ASC-Net: Adversarial-based Selective Network for Unsupervised Anomaly Segmentation
  • Bounding Box Tightness Prior for Weakly Supervised Image Segmentation
  • Cell Detection from Imperfect Annotation by Pseudo Label Selection Using P-classification
  • Combining Attention-based Multiple Instance Learning and Gaussian Processes for CT Hemorrhage Detection
  • Conditional GAN with an Attention-based Generator and a 3D Discriminator for 3D Medical Image Generation
  • Consistent Segmentation of Longitudinal Brain MR Images with Spatio-Temporal Constrained Networks
  • CPNet: Cycle Prototype Network for Weakly-supervised 3D Renal Chamber Segmentation
  • Deep Simulation of Facial Appearance Changes Following Craniomaxillofacial Bony Movements in Orthognathic Surgical Planning
  • DeepOPG: Improving Orthopantomogram Finding Summarization with Weak Supervision
  • DT-MIL: Deformable Transformer for Multi-instance Learning on Histopathological Image
  • Energy-Based Supervised Hashing for Multimorbidity Image Retrieval
  • Flip Learning: Erase to Segment
  • Generative Self-training for Cross-domain Unsupervised Tagged-to-Cine MRI Synthesis
  • Hybrid Supervision Learning for Whole Slide Image Classification
  • Implicit Neural Distance Representation for Unsupervised and Supervised Classification of Complex Anatomies
  • Improving Pneumonia Localization via Cross-Attention on Medical Images and Reports
  • Inter Extreme Points Geodesics for End-to-End Weakly Supervised Image Segmentation
  • Label-Free Physics-Informed Image Sequence Reconstruction with Disentangled Spatial-Temporal Modeling
  • Labels-set Loss Functions for Partial Supervision: Application to Fetal Brain 3D MRI Parcellation
  • Learning Whole-Slide Segmentation from Inexact and Incomplete Labels using Tissue Graphs
  • Learning with Noise: Mask-guided Attention Model for Weakly Supervised Nuclei Segmentation
  • Leveraging Auxiliary Information from EMR for Weakly Supervised Pulmonary Nodule Detection
  • Local-global Dual Perception based Deep Multiple Instance Learning for Retinal Disease Classification
  • M-SEAM-NAM: Multi-instance Self-supervised Equivalent Attention Mechanism with Neighborhood Affinity Module for Double Weakly Supervised Segmentation of COVID-19
  • Multi-modal Multi-instance Learning using Weakly Correlated Histopathological Images and Tabular Clinical Information
  • Multimodal Representation Learning via Maximization of Local Mutual Information
  • Multimodal Sensing Guidewire for C-arm Navigation with Random UV Enhanced Optical Sensors using Spatio-temporal Networks
  • Multiple Instance Learning with Auxiliary Task Weighting for Multiple Myeloma Classification
  • Observational Supervision for Medical Image Classification using Gaze Data
  • OXnet: Deep Omni-supervised Thoracic Disease Detection from Chest X-rays
  • Predicting Symptoms from Multiphasic MRI via Multi-Instance Attention Learning for Hepatocellular Carcinoma Grading
  • Real-Time Rotated Convolutional Descriptor for Surgical Environments
  • Superpixel-guided Iterative Learning from Noisy Labels for Medical Image Segmentation
  • Trainable summarization to improve breast tomosynthesis classification
  • Training Deep Networks for Prostate Cancer Diagnosis Using Coarse Histopathological Labels
  • U-DuDoNet: Unpaired dual-domain network for CT metal artifact reduction
  • Uncertainty-Guided Progressive GANs for Medical Image Translation
  • Weakly supervised pan-cancer segmentation tool
  • Weakly-Supervised Ultrasound Video Segmentation with Minimal Annotations
  • Weakly-Supervised Universal Lesion Segmentation with Regional Level Set Loss
  • Whole Slide Images are 2D Point Clouds: Context-Aware Survival Prediction using Patch-based Graph Convolutional Networks

    • Medical Robotics and Haptics

  • Acoustic-based Spatio-temporal Learning for Press-fit Evaluation of Femoral Stem Implants
  • Prototypical Interaction Graph for Unsupervised Domain Adaptation in Surgical Instrument Segmentation

    • Modalities - Biophotonics

  • A Line to Align: Deep Dynamic Time Warping for Retinal OCT Segmentation
  • Efficient neural network approximation of robust PCA for automated analysis of calcium imaging data
  • Interhemispheric functional connectivity in the primary motor cortex distinguishes between training on a physical and a virtual surgical simulator

    • Modalities - CT

  • 3D Brain Midline Delineation for Hematoma Patients
  • 3D-UCaps: 3D Capsules Unet for Volumetric Image Segmentation
  • 4D-CBCT Registration with a FBCT-derived Plug-and-Play Feasibility Regularizer
  • 4D-Foot: A fully automated pipeline of four-dimensional analysis of the foot bones using bi-plane X-ray video and CT
  • A Novel Hybrid Convolutional Neural Network for Accurate Organ Segmentation in 3D Head and Neck CT Images
  • A Segmentation-Assisted Model for Universal Lesion Detection with Partial Labels
  • A self-supervised deep framework for reference bony shape estimation in orthognathic surgical planning
  • Airway Anomaly Detection by Graph Neural Network
  • An Interpretable Approach to Automated Severity Scoring in Pelvic Trauma
  • Anatomy-Constrained Contrastive Learning for Synthetic Segmentation without Ground-truth
  • ASC-Net: Adversarial-based Selective Network for Unsupervised Anomaly Segmentation
  • Asymmetric 3D Context Fusion for Universal Lesion Detection
  • Atlas-Based Segmentation of Intracochlear Anatomy in Metal Artifact Affected CT Images of the Ear with Co-trained Deep Neural Networks
  • Attention based CNN-LSTM Network for Pulmonary Embolism Prediction on Chest Computed Tomography Pulmonary Angiograms
  • Beyond COVID-19 Diagnosis: Prognosis with Hierarchical Graph Representation Learning
  • CA-Net: Leveraging Contextual Features for Lung Cancer Prediction
  • Coarse-to-fine Segmentation of Organs at Risk in Nasopharyngeal Carcinoma Radiotherapy
  • Co-Graph Attention Reasoning based Imaging and Clinical Features Integration for Lymph Node Metastasis Prediction
  • Combining Attention-based Multiple Instance Learning and Gaussian Processes for CT Hemorrhage Detection
  • Conditional Training with Bounding Map for Universal Lesion Detection
  • Context-aware virtual adversarial training for anatomically-plausible segmenation
  • Contrastive Learning of Relative Position Regression for One-Shot Object Localization in 3D Medical Images
  • Contrastive Pre-training and Representation Distillation for Medical Visual Question Answering Based on Radiology Images
  • CoTr: Efficiently Bridging CNN and Transformer for 3D Medical Image Segmentation
  • CPNet: Cycle Prototype Network for Weakly-supervised 3D Renal Chamber Segmentation
  • Deep Open Snake Tracker for Vessel Tracing
  • DeepStationing: Thoracic Lymph Node Station Parsing in CT Scans using Anatomical Context Encoding and Key Organ Auto-Search
  • Detecting when pre-trained nnU-Net models fail silently for Covid-19 lung lesion segmentation
  • Distilling effective supervision for robust medical image segmentation with noisy labels
  • Distortion Energy for Deep Learning-based Volumetric Finite Element Mesh Generation for Aortic Valves
  • Do we need complex image features to personalize treatment of patients with locally advanced rectal cancer?
  • Dual-Consistency Semi-Supervised Learning with Uncertainty Quantification for COVID-19 Lesion Segmentation from CT Images
  • Dual-Domain Adaptive-Scaling Non-Local Network for CT Metal Artifact Reduction
  • EMA: Auditing Data Removal from Trained Models
  • Facial and cochlear nerves characterization using deep reinforcement learning for landmark detection
  • Federated Whole Prostate Segmentation in MRI with Personalized Neural Architectures
  • Hierarchical Self-Supervised Learning for Medical Image Segmentation Based on Multi-Domain Data Aggregation
  • Improving Generalizability in Limited-Angle CT Reconstruction with Sinogram Extrapolation
  • Incorporating Isodose Lines and Gradient Information via Multi-task Learning for Dose Prediction in Radiotherapy
  • InDuDoNet: An Interpretable Dual Domain Network for CT Metal Artifact Reduction
  • Interactive smoothing parameter optimization in DBT Reconstruction using Deep learning
  • Intracerebral Haemorrhage Growth Prediction Based on Displacement Vector Field and Clinical Metadata
  • Joint Segmentation and Quantification of Main Coronary Vessels Using Dual-branch Multi-scale Attention Network
  • kCBAC-Net: Deeply Supervised Complete Bipartite Networks with Asymmetric Convolutions for Medical Image Segmentation
  • Learnable Multi-scale Fourier Interpolation for Sparse View CT Image Reconstruction
  • Learning Consistency- and Discrepancy-Context for 2D Organ Segmentation
  • Lesion Segmentation and RECIST Diameter Prediction via Click-driven Attention and Dual-path Connection
  • LuMiRa: An Integrated Lung Deformation Atlas and 3D-CNN model of Infiltrates for COVID-19 Prognosis
  • Lung Cancer Risk Estimation with Incomplete Data: A Joint Missing Imputation Perspective
  • Modality-aware Mutual Learning for Multi-modal Medical Image Segmentation
  • M-SEAM-NAM: Multi-instance Self-supervised Equivalent Attention Mechanism with Neighborhood Affinity Module for Double Weakly Supervised Segmentation of COVID-19
  • MT-UDA: Towards Unsupervised Cross-Modality Medical Image Segmentation with Limited Source Labels
  • Multi-phase Liver Tumor Segmentation with Spatial Aggregation and Uncertain Region Inpainting
  • Noisy Labels are Treasure: Mean-Teacher-Assisted Confident Learning for Hepatic Vessel Segmentation
  • NucMM Dataset: 3D Neuronal Nuclei Instance Segmentation at Sub-Cubic Millimeter Scale
  • OLVA: Optimal Latent Vector Alignment for Unsupervised Domain Adaptation in Medical Image Segmentation
  • Pancreas CT Segmentation by Predictive Phenotyping
  • Patient-specific virtual spine straightening and vertebra inpainting: An automatic framework for osteoplasty planning
  • Personalized CT Organ Dose Estimation from Scout Images
  • Phase-independent Latent Representation for Cardiac Shape Analysis
  • Point-Unet: A Context-aware Point-based Neural Network for Volumetric Segmentation
  • Predicting Esophageal Fistula Risks Using a Multimodal Self-Attention Network
  • Reciprocal Learning for Semi-supervised Segmentation
  • Refined Local-imbalance-based Weight for Airway Segmentation in CT
  • ReSGAN: Intracranial Hemorrhage Segmentation with Residuals of Synthetic Brain CT Scans
  • RibSeg Dataset and Strong Point Cloud Baselines for Rib Segmentation from CT Scans
  • SA-GAN: Structure-Aware GAN for Organ-Preserving Synthetic CT Generation
  • SAME: Deformable Image Registration based on Self-supervised Anatomical Embeddings
  • Selective Learning from External Data for CT Image Segmentation
  • Semi-supervised Contrastive Learning for Label-efficient Medical Image Segmentation
  • Semi-Supervised Unpaired Multi-Modal Learning for Label-Efficient Medical Image Segmentation
  • Sequential Gaussian Process Regression for Simultaneous Pathology Detection and Shape Reconstruction
  • Sequential Learning on Liver Tumor Boundary Semantics and Prognostic Biomarker Mining
  • Sequential Lung Nodule Synthesis using Attribute-guided Generative Adversarial Networks
  • SGNet: Structure-aware Graph-based Network for Airway Semantic Segmentation
  • SPARTA: An Integrated Stability, Discriminability, and Sparsity based Radiomic Feature Selection Approach
  • Spectral Embedding Approximation and Descriptor Learning for Craniofacial Volumetric Image Correspondence
  • Spine-Transformers: Vertebra Detection and Localization in Arbitrary Field-of-View Spine CT with Transformers
  • SyNCCT: Synthetic Non-Contrast Images of the Brain from Single-Energy Computed Tomography Angiography
  • TarGAN: Target-Aware Generative Adversarial Networks for Multi-modality Medical Image Translation
  • Task-Oriented Low-Dose CT Image Denoising
  • The Power of Proxy Data and Proxy Networks for Hyper-Parameter Optimization for Medical Image Segmentation
  • Towards a non-invasive diagnosis of portal hypertension based on an Eulerian CFD model with diffuse boundary conditions
  • Towards Robust General Medical Image Segmentation
  • TransCT: Dual-path Transformer for Low Dose Computed Tomography
  • Transformer Network for Significant Stenosis Detection in CCTA of Coronary Arteries
  • TumorCP: A Simple but Effective Object-Level Data Augmentation for Tumor Segmentation
  • U-DuDoNet: Unpaired dual-domain network for CT metal artifact reduction
  • Uncertainty-Guided Progressive GANs for Medical Image Translation
  • Unsupervised Contrastive Learning of Radiomics and Deep Features for Label-Efficient Tumor Classification
  • Unsupervised Domain Adaptation for Small Bowel Segmentation using Disentangled Representation
  • Using Multiple Images and Contours for Deformable 3D-2D Registration of a Preoperative CT in Laparoscopic Liver Surgery
  • VertNet: Accurate Vertebra Localization and Identification Network from CT Images
  • Weakly-Supervised Universal Lesion Segmentation with Regional Level Set Loss
  • Whole Heart Mesh Generation For Image-Based Computational Simulations By Learning Free-From Deformations

    • Modalities - EEG/ECG

  • Cardiac Transmembrane Potential Imaging with GCN Based Iterative Soft Threshold Network
  • Deep Neural Dynamic Bayesian Networks applied to EEG sleep spindles modeling
  • Label-Free Physics-Informed Image Sequence Reconstruction with Disentangled Spatial-Temporal Modeling

    • Modalities - Histopathology

  • A Multi-attribute Controllable Generative Model for Histopathology Image Synthesis
  • A Principled Approach to Failure Analysis and Model Repairment: Demonstration in Medical Imaging
  • Accounting for Dependencies in Deep Learning based Multiple Instance Learning for Whole Slide Imaging
  • Adversarial learning of cancer tissue representations
  • Cells are Actors: Social Network Analysis with Classical ML for SOTA Histology Image Classification
  • Contrastive Learning Based Stain Normalization Across Multiple Tumor Histopathology
  • Deep Orthogonal Fusion: Multimodal Prognostic Biomarker Discovery Integrating Radiology, Pathology, Genomic, and Clinical Data
  • DT-MIL: Deformable Transformer for Multi-instance Learning on Histopathological Image
  • Early Detection of Liver Fibrosis Using Graph Convolutional Networks
  • Focusing on Clinically Interpretable Features: Selective Attention Regularization for Liver Biopsy Image Classification
  • From Pixel to Whole Slide: Automatic Detection of Microvascular Invasion in Hepatocellular Carcinoma on Histopathological Image via Cascaded Networks
  • GloFlow: Whole Slide Image Stitching from Video using Optical Flow and Global Image Alignment
  • GQ-GCN: Group Quadratic Graph Convolutional Network for Classification of Histopathological Images
  • Hierarchical Attention Guided Framework for Multi-resolution Collaborative Whole Slide Image Segmentation
  • Hierarchical graph pathomic network for progression free survival prediction
  • Hierarchical Phenotyping and Graph Modeling of Spatial Architecture in Lymphoid Neoplasms
  • Hybrid Aggregation Network for Survival Analysis from Whole Slide Histopathological Images
  • Hybrid Supervision Learning for Whole Slide Image Classification
  • Instance-aware Feature Alignment for Cross-domain Cell Nuclei Detection in Histopathology Images
  • Instance-based Vision Transformer for Subtyping of Papillary Renal Cell Carcinoma in Histopathological Image
  • Integration of Patch Features through Self-Supervised Learning and Transformer for Survival Analysis on Whole Slide Images
  • Learning Visual Features by Colorization for Slide-Consistent Survival Prediction from Whole Slide Images
  • Learning Whole-Slide Segmentation from Inexact and Incomplete Labels using Tissue Graphs
  • Learning with Noise: Mask-guided Attention Model for Weakly Supervised Nuclei Segmentation
  • MetaCon: Meta Contrastive Learning for Microsatellite Instability Detection
  • Multi-modal Multi-instance Learning using Weakly Correlated Histopathological Images and Tabular Clinical Information
  • Non-parametric vignetting correction for sparse spatial transcriptomics images
  • Nuclei Grading of Clear Cell Renal Cell Carcinoma in Histopathological Image by Composite High-Resolution Network
  • Pay Attention with Focus: A Novel Learning Scheme for Classification of Whole Slide Images
  • Positive-unlabeled Learning for Cell Detection in Histopathology Images with Incomplete Annotations
  • Ranking loss: A ranking-based deep neural network for colorectal cancer grading in pathology images
  • Renal Cell Carcinoma Classification from Vascular Morphology
  • Self-supervised visual representation learning for histopathological images
  • Semi-supervised Adversarial Learning for Stain Normalisation in Histopathology Images
  • Sharpening Local Interpretable Model-agnostic Explanations for Histopathology: Improved Understandability and Reliability
  • Spatial Attention-based Deep Learning System for Breast Cancer Pathological Complete Response Prediction with Serial Histopathology Images in Multiple Stains
  • SSLP: Spatial Guided Self-supervised Learning on Pathological Images
  • Stain Mix-up: Unsupervised Domain Generalization for Histopathology Images
  • Structure-Preserving Multi-Domain Stain Color Augmentation using Style-Transfer with Disentangled Representations
  • Survival Prediction Based on Histopathology Imaging and Clinical Data: A Novel, Whole Slide CNN Approach
  • TransPath: Transformer-based Self-supervised Learning for Histopathological Image Classification
  • Weakly supervised pan-cancer segmentation tool
  • Weakly Supervised Registration of Prostate MRI and Histopathology Images
  • Whole Slide Images are 2D Point Clouds: Context-Aware Survival Prediction using Patch-based Graph Convolutional Networks

    • Modalities - MRI

  • 2.5D Thermometry Maps for MRI-guided Tumor Ablation
  • 3D-UCaps: 3D Capsules Unet for Volumetric Image Segmentation
  • A Deep Network for Joint Registration and Parcellation of Cortical Surfaces
  • A hybrid attention ensemble framework for zonal prostate segmentation
  • A spherical convolutional neural network for white matter structure imaging via diffusion MRI
  • A Structural Causal Model MR Images of Multiple Sclerosis
  • A Unified Hyper-GAN Model for Unpaired Multi-contrast MR Image Translation
  • Acceleration by deep-learnt sharing of superfluous information in multi-contrast MRI
  • ACN: Adversarial Co-training Network for Brain Tumor Segmentation with Missing Modalities
  • Active Cortex Tractography
  • Adapting Off-the-Shelf Source Segmenter for Target Medical Image Segmentation
  • Adaptive Squeeze-and-Shrink Image Denoising for Improving Deep Detection of Cerebral Microbleeds
  • AMINN: Autoencoder-based Multiple Instance Neural Network Improves Outcome Prediction of Multifocal Liver Metastases
  • Anatomy of Domain Shift Impact on U-Net Layers in MRI Segmentation
  • Anatomy-Constrained Contrastive Learning for Synthetic Segmentation without Ground-truth
  • ASC-Net: Adversarial-based Selective Network for Unsupervised Anomaly Segmentation
  • Bayesian Atlas Building with Hierarchical Priors for Subject-specific Regularization
  • Building Dynamic Hierarchical Brain Networks and Capturing Transient Meta-states for Early Mild Cognitive Impairment Diagnosis
  • CarveMix: A Simple Data Augmentation Method for Brain Lesion Segmentation
  • Collaborative Image Synthesis and Disease Diagnosis for Classification of Neurodegenerative Disorders with Incomplete Multi-modal Neuroimages
  • Comprehensive Importance-based Selective Regularization for Continual Segmentation Across Multiple Sites
  • Confidence-aware Cascaded Network for Fetal Brain Segmentation on MR Images
  • Consistent Segmentation of Longitudinal Brain MR Images with Spatio-Temporal Constrained Networks
  • Construction of Longitudinally Consistent 4D Infant Cerebellum Atlases based on Deep Learning
  • Context-aware virtual adversarial training for anatomically-plausible segmenation
  • Continuous-Time Deep Glioma Growth Models
  • Contrastive Pre-training and Representation Distillation for Medical Visual Question Answering Based on Radiology Images
  • Controllable cardiac synthesis via disentangled anatomy arithmetic
  • Cooperative Training and Latent Space Data Augmentation for Robust Medical Image Segmentation
  • Cost-Sensitive Meta-Learning for Progress Prediction of Subjective Cognitive Decline with Brain Structural MRI
  • Cross-modal Attention for MRI and Ultrasound Volume Registration
  • Deep Fiber Clustering: Anatomically Informed Unsupervised Deep Learning for Fast and Effective White Matter Parcellation
  • Deep J-Sense: Accelerated MRI Reconstruction via Unrolled Alternating Optimization
  • Deep Open Snake Tracker for Vessel Tracing
  • Deep Orthogonal Fusion: Multimodal Prognostic Biomarker Discovery Integrating Radiology, Pathology, Genomic, and Clinical Data
  • Demystifying T1-MRI to FDG18-PET Image Translation via Representational Similarity
  • Detecting Brain State Changes by Geometric Deep Learning of Functional Dynamics on Riemannian Manifold
  • Distilling effective supervision for robust medical image segmentation with noisy labels
  • Do we need complex image features to personalize treatment of patients with locally advanced rectal cancer?
  • Duo-SegNet: Adversarial Dual-Views for Semi-Supervised Medical Image Segmentation
  • Equivariant Filters for Efficient Tracking in 3D Imaging
  • Estimation of spontaneous neuronal activity using homomorphic filtering
  • Exploring the Functional Difference of Gyri/Sulci via Hierarchical Interpretable Autoencoder
  • Fairness in Cardiac MR Image Analysis: An Investigation of Bias Due to Data Imbalance in Deep Learning Based Segmentation
  • Fast Magnetic Resonance Imaging on Regions of Interest: From Sensing to Reconstruction
  • Generalised Super Resolution for Quantitative MRI Using Self-Supervised Mixture of Experts
  • Generative Self-training for Cross-domain Unsupervised Tagged-to-Cine MRI Synthesis
  • Harmonization with Flow-based Causal Inference
  • Hierarchical Self-Supervised Learning for Medical Image Segmentation Based on Multi-Domain Data Aggregation
  • Highly Reproducible Whole Brain Parcellation in Individuals via Voxel Annotation with Fiber Clusters
  • Imbalance-Aware Self-Supervised Learning for 3D Radiomic Representations
  • Improved Brain Lesion Segmentation with Anatomical Priors from Healthy Subjects
  • Inter Extreme Points Geodesics for End-to-End Weakly Supervised Image Segmentation
  • Interpretable deep learning for multimodal super-resolution of medical images
  • IREM: High-Resolution Magnetic Resonance Image Reconstruction via Implicit Neural Representation
  • Joint Motion Correction and Super Resolution for Cardiac Segmentation via Latent Optimisation
  • Joint PVL Detection and Manual Ability Classification using Semi-Supervised Multi-task Learning
  • Learning 4D Infant Cortical Surface Atlas with Unsupervised Spherical Networks
  • Learning Spatiotemporal Probabilistic Atlas of Fetal Brains with Anatomically Constrained Registration Network
  • Learning to Predict Error for MRI Reconstruction
  • LG-Net: Lesion Gate Network for Multiple Sclerosis Lesion Inpainting
  • Local Morphological Measures Confirm that Folding within Small Partitions of the Human Cortex Follows Universal Scaling Law
  • Longitudinal Correlation Analysis for Decoding Multi-Modal Brain Development
  • Longitudinal self-supervision to disentangle inter-patient variability from disease progression
  • Medical Image Registration Based on Uncoupled Learning and Accumulative Enhancement
  • Memory-efficient Learning for High-dimensional MRI Reconstruction
  • mfTrans-Net: Quantitative Measurement of Hepatocellular Carcinoma via Multi-Function Transformer Regression Network
  • Modality Completion via Gaussian Process Prior Variational Autoencoders for Multi-Modal Glioma Segmentation
  • Modality-aware Mutual Learning for Multi-modal Medical Image Segmentation
  • MouseGAN: GAN-Based Multiple MRI Modalities Synthesis and Segmentation for Mouse Brain Structures
  • MT-UDA: Towards Unsupervised Cross-Modality Medical Image Segmentation with Limited Source Labels
  • Multi-Contrast MRI Super-Resolution via a Multi-Stage Integration Network
  • Multi-Head GAGNN: A Multi-Head Guided Attention Graph Neural Network for Modeling Spatio-Temporal Patterns of Holistic Brain Functional Networks
  • Multimodal MRI Acceleration via Deep Cascading Networks with Peer-layer-wise Dense Connections
  • Multiple Instance Learning with Auxiliary Task Weighting for Multiple Myeloma Classification
  • Multi-Task, Multi-Domain Deep Segmentation with Shared Representations and Contrastive Regularization for Sparse Pediatric Datasets
  • Noise Mapping and Removal in Complex-Valued Multi-Channel MRI via Optimal Shrinkage of Singular Values
  • Non-invasive Assessment of Hepatic Venous Pressure Gradient (HVPG) Based on MR Flow Imaging and Computational Fluid Dynamics
  • OLVA: Optimal Latent Vector Alignment for Unsupervised Domain Adaptation in Medical Image Segmentation
  • Orthogonal Ensemble Networks for Biomedical Image Segmentation
  • Over-and-Under Complete Convolutional RNN for MRI Reconstruction
  • Patch-Free 3D Medical Image Segmentation Driven by Super-Resolution Technique and Self-Supervised Guidance
  • Personalized Matching and Analysis of Cortical Folding Patterns via Patch-Based Intrinsic Brain Mapping
  • Personalized Respiratory Motion Model Using Conditional Generative Networks for MR-Guided Radiotherapy
  • Point-Unet: A Context-aware Point-based Neural Network for Volumetric Segmentation
  • Predicting Symptoms from Multiphasic MRI via Multi-Instance Attention Learning for Hepatocellular Carcinoma Grading
  • Real-Time Mapping of Tissue Properties for Magnetic Resonance Fingerprinting
  • Reciprocal Learning for Semi-supervised Segmentation
  • Reference-Relation Guided Autoencoder with Deep CCA Restriction for Awake-to-Sleep Brain Functional Connectome Prediction
  • Region Ensemble Network for MCI Conversion Prediction With a Relation Regularized Loss
  • Rician noise estimation for 3D Magnetic Resonance Images based on Benford's Law
  • SA-GAN: Structure-Aware GAN for Organ-Preserving Synthetic CT Generation
  • Segmentation of Left Atrial MR Images via Self-supervised Semi-supervised Meta-learning
  • SegRecon: Learning Joint Brain Surface Reconstruction and Segmentation from Images
  • Self-Supervised Learning for MRI Reconstruction with a Parallel Network Training Framework
  • Self-supervised Lesion Change Detection and Localisation in Longitudinal Multiple Sclerosis Brain Imaging
  • Self-Supervised Longitudinal Neighbourhood Embedding
  • Self-Supervised Multi-Modal Alignment For Whole Body Medical Imaging
  • Semi-supervised Contrastive Learning for Label-efficient Medical Image Segmentation
  • Semi-supervised Left Atrium Segmentation with Mutual Consistency Training
  • Semi-Supervised Unpaired Multi-Modal Learning for Label-Efficient Medical Image Segmentation
  • SPARTA: An Integrated Stability, Discriminability, and Sparsity based Radiomic Feature Selection Approach
  • SpineGEM: A Hybrid-Supervised Model Generation Strategy Enabling Accurate Spine Disease Classification with a Small Training Dataset
  • Stochastic 4D Flow Vector-Field Signatures: A new approach for comprehensive 4D Flow MRI quantification
  • STRESS: Super-Resolution for Dynamic Fetal MRI using Self-Supervised Learning
  • Style Curriculum Learning for Robust Medical Image Segmentation
  • Style Transfer Using Generative Adversarial Networks for Multi-Site MRI Harmonization
  • Surface-Guided Image Fusion for Preserving Cortical Details in Human Brain Templates
  • TarGAN: Target-Aware Generative Adversarial Networks for Multi-modality Medical Image Translation
  • Task Transformer Network for Joint MRI Reconstruction and Super-Resolution
  • TEDS-Net: Enforcing Diffeomorphisms in Spatial Transformers to Guarantee Topology Preservation in Segmentations
  • Temporal Feature Fusion with Sampling Pattern Optimization for Multi-echo Gradient Echo Acquisition and Image Reconstruction
  • Tensor-based Multi-index Representation Learning for Major Depression Disorder Detection with Resting-state fMRI
  • The Power of Proxy Data and Proxy Networks for Hyper-Parameter Optimization for Medical Image Segmentation
  • Topological Learning and Its Application to Multimodal Brain Network Integration
  • Topological Receptive Field Model for Human Retinotopic Mapping
  • Towards Robust General Medical Image Segmentation
  • Towards Ultrafast MRI via Extreme k-Space Undersampling and Superresolution
  • Training Automatic View Planner for Cardiac MR Imaging via Self-Supervision by Spatial Relationship between Views
  • TransBTS: Multimodal Brain Tumor Segmentation Using Transformer
  • TVnet: Automated Time-Resolved Tracking of the Tricuspid Valve Plane in MRI Long-Axis Cine Images with a Dual-Stage Deep Learning Pipeline
  • Two-Stage Self-Supervised Cycle-Consistency Network for Reconstruction of Thin-Slice MR Images
  • Uncertainty Aware Deep Reinforcement Learning for Anatomical Landmark Detection in Medical Images
  • Uncertainty-Guided Progressive GANs for Medical Image Translation
  • Universal Undersampled MRI Reconstruction
  • Using Multiple Images and Contours for Deformable 3D-2D Registration of a Preoperative CT in Laparoscopic Liver Surgery
  • UTNet: A Hybrid Transformer Architecture for Medical Image Segmentation
  • Weakly Supervised Registration of Prostate MRI and Histopathology Images

    • Modalities - Microscopy

  • 2D Histology Meets 3D Topology: Cytoarchitectonic Brain Mapping with Graph Neural Networks
  • A Deep Learning Bidirectional Temporal Tracking Algorithm for Automated Blood Cell Counting from Non-invasive Capillaroscopy Videos
  • A Multi-Branch Hybrid Transformer Network for Corneal Endothelial Cell Segmentation
  • Annotation-efficient Cell Counting
  • Automated Malaria Cells Detection from Blood Smears under Severe Class Imbalance via Importance-aware Balanced Group Softmax
  • Automating Embryo Development Stage Detection in Time-Lapse Imaging with Synergic Loss and Temporal Learning
  • CA^{2.5}-Net Nuclei Segmentation Framework with a Microscopy Cell Benchmark Collection
  • Cell Detection from Imperfect Annotation by Pseudo Label Selection Using P-classification
  • Cell Detection in Domain Shift Problem Using Pseudo-Cell-Position Heatmap
  • Developmental Stage Classification of Embryos Using Two-Stream Neural Network with Linear-Chain Conditional Random Field
  • Duo-SegNet: Adversarial Dual-Views for Semi-Supervised Medical Image Segmentation
  • Efficient neural network approximation of robust PCA for automated analysis of calcium imaging data
  • Generalizing Nucleus Recognition Model in Multi-source Ki67 Immunohistochemistry Stained Images via Domain-specific Pruning
  • Joint Optimization of Hadamard Sensing and Reconstruction in Compressed Sensing Fluorescence Microscopy
  • Learning Neuron Stitching for Connectomics
  • Multi-StyleGAN: Towards Image-Based Simulation of Time-Lapse Live-Cell Microscopy
  • Non-parametric vignetting correction for sparse spatial transcriptomics images
  • NucMM Dataset: 3D Neuronal Nuclei Instance Segmentation at Sub-Cubic Millimeter Scale
  • Parallel Capsule Networks for Classification of White Blood Cells
  • Relational Subsets Knowledge Distillation for Long-tailed Retinal Diseases Recognition
  • RLP-Net: Recursive Light Propagation Network for 3-D Virtual Refocusing
  • Semi-supervised Cell Detection in Time-lapse Images Using Temporal Consistency
  • Uncertainty-Aware Label Rectification for Domain Adaptive Mitochondria Segmentation
  • Unsupervised Network Learning for Cell Segmentation

    • Modalities - PET/SPECT

  • 3D Transformer-GAN for High-quality PET Reconstruction
  • Anatomy-Constrained Contrastive Learning for Synthetic Segmentation without Ground-truth
  • Collaborative Image Synthesis and Disease Diagnosis for Classification of Neurodegenerative Disorders with Incomplete Multi-modal Neuroimages
  • Demystifying T1-MRI to FDG18-PET Image Translation via Representational Similarity
  • Synthesizing Multi-Tracer PET Images for Alzheimer's Disease Patients using a 3D Unified Anatomy-aware Cyclic Adversarial Network
  • Targeted Gradient Descent: A Novel Method for Convolutional Neural Networks Fine-tuning and Online-learning
  • Uncertainty-Guided Progressive GANs for Medical Image Translation

    • Modalities - Text (clinical/radiology reports)

  • AlignTransformer: Hierarchical Alignment of Visual Regions and Disease Tags for Medical Report Generation
  • AnaXNet: Anatomy Aware Multi-label Finding Classification in Chest X-ray
  • Contrastive Pre-training and Representation Distillation for Medical Visual Question Answering Based on Radiology Images
  • Improving Pneumonia Localization via Cross-Attention on Medical Images and Reports
  • Multi-modal Multi-instance Learning using Weakly Correlated Histopathological Images and Tabular Clinical Information
  • Multimodal Multitask Deep Learning for X-Ray Image Retrieval
  • Multimodal Representation Learning via Maximization of Local Mutual Information
  • RATCHET: Medical Transformer for Chest X-ray Diagnosis and Reporting
  • Surgical Instruction Generation with Transformers
  • Survival Prediction Based on Histopathology Imaging and Clinical Data: A Novel, Whole Slide CNN Approach
  • Text2Brain: Synthesis of Brain Activation Maps from Free-form Text Query
  • Using Causal Analysis for Conceptual Deep Learning Explanation
  • Variational Topic Inference for Chest X-Ray Report Generation

    • Modalities - Ultrasound

  • A Neural Framework for Multi-Variable Lesion Quantification Through B-mode Style Transfer
  • A Principled Approach to Failure Analysis and Model Repairment: Demonstration in Medical Imaging
  • A Spatial Guided Self-supervised Clustering Network for Medical Image Segmentation
  • AutoFB: Automating Fetal Biometry Estimation from Standard Ultrasound Planes
  • Content-Preserving Unpaired Translation from Simulated to Realistic Ultrasound Images
  • Cross-modal Attention for MRI and Ultrasound Volume Registration
  • DeepMitral: Fully Automatic 3D Echocardiography Segmentation for Patient Specific Mitral Valve Modelling
  • Detecting Hypo-plastic Left Heart Syndrome in Fetal Ultrasound via Disease-specific Atlas Maps
  • EchoCP: An Echocardiography Dataset in Contrast Transthoracic Echocardiography for Patent Foramen Ovale Diagnosis
  • EllipseNet: Anchor-Free Ellipse Detection for Automatic Cardiac Biometrics in Fetal Echocardiography
  • End-to-end Ultrasound Frame to Volume Registration
  • Enhanced Breast Lesion Classification via Knowledge Guided Cross-Modal and Semantic Data Augmentation
  • Identifying Quantitative and Explanatory Tumor Indexes from Dynamic Contrast Enhanced Ultrasound
  • Interactive segmentation via deep learning and B-spline explicit active surfaces
  • kCBAC-Net: Deeply Supervised Complete Bipartite Networks with Asymmetric Convolutions for Medical Image Segmentation
  • Learned super resolution ultrasound for improved breast lesion characterization
  • Learning from Subjective Ratings Using Auto-Decoded Deep Latent Embeddings
  • Learning-based attenuation quantification in abdominal ultrasound
  • MBFF-Net: Multi-Branch Feature Fusion Network for Carotid Plaque Segmentation in Ultrasound
  • Multi-frame Attention Network for Left Ventricle Segmentation in 3D Echocardiography
  • Quantitative Assessments for Ultrasound Probe Calibration
  • Residual Feedback Network for Breast Lesion Segmentation in Ultrasound Image
  • Rethinking Ultrasound Augmentation: A Physics-Inspired Approach
  • Self Context and Shape Prior for Sensorless Freehand 3D Ultrasound Reconstruction
  • Towards Efficient Human-Machine Collaboration: Real-Time Correction Effort Prediction for Ultrasound Data Acquisition
  • Training Deep Networks for Prostate Cancer Diagnosis Using Coarse Histopathological Labels
  • TUN-Det: A Novel Network for Thyroid Ultrasound Nodule Detection
  • Ultrasound Video Transformers for Cardiac Ejection Fraction Estimation
  • Unsupervised Contrastive Learning of Radiomics and Deep Features for Label-Efficient Tumor Classification
  • USCL: Pretraining Deep Ultrasound Image Diagnosis Model through Video Contrastive Representation Learning
  • Visual-Assisted Probe Movement Guidance for Obstetric Ultrasound Scanning using Landmark Retrieval
  • Weakly-Supervised Ultrasound Video Segmentation with Minimal Annotations

    • Modalities - Video

  • A Deep Learning Bidirectional Temporal Tracking Algorithm for Automated Blood Cell Counting from Non-invasive Capillaroscopy Videos
  • Adversarial Domain Feature Adaptation for Bronchoscopic Depth Estimation
  • Depth Estimation for Colonoscopy Images with Self-supervised Learning from Videos
  • Detection of critical structures in laparoscopic cholecystectomy using label relaxation and self-supervision
  • Developmental Stage Classification of Embryos Using Two-Stream Neural Network with Linear-Chain Conditional Random Field
  • EchoCP: An Echocardiography Dataset in Contrast Transthoracic Echocardiography for Patent Foramen Ovale Diagnosis
  • Effective semantic segmentation in Cataract surgery: What matters most?
  • EMDQ-SLAM: Real-time High-resolution Reconstruction of Soft Tissue Surface from Stereo Laparoscopy Videos
  • Few Trust Data Guided Annotation Refinement for Upper Gastrointestinal Anatomy Recognition
  • FoldIt: Haustral Folds Detection and Segmentation in Colonoscopy Videos
  • Hepatocellular Carcinoma Segmentation from Digital Subtraction Angiography Videos using Learnable Temporal Difference
  • LDPolypVideo Benchmark: A Large-scale Colonoscopy Video Dataset of Diverse Polyps
  • LensID: A CNN-RNN-Based Framework Towards Lens Irregularity Detection in Cataract Surgery Videos
  • Multi-frame Collaboration for Effective Endoscopic Video Polyp Detection via Spatial-Temporal Feature Transformation
  • Multi-View Surgical Video Action Detection via Mixed Global View Attention
  • OperA: Attention-Regularized Transformers for Surgical Phase Recognition
  • Real-Time Rotated Convolutional Descriptor for Surgical Environments
  • SurgeonAssist-Net: Towards Context-Aware Head-Mounted Display-Based Augmented Reality for Surgical Guidance
  • Surgical Workflow Anticipation using Instrument Interaction
  • Task Fingerprinting for Meta Learning in Biomedical Image Analysis
  • Transfer Learning of Deep Spatiotemporal Networks to Model Arbitrarily Long Videos of Seizures
  • Ultrasound Video Transformers for Cardiac Ejection Fraction Estimation
  • Whole Heart Mesh Generation For Image-Based Computational Simulations By Learning Free-From Deformations

    • Modalities - other

  • 4D-Foot: A fully automated pipeline of four-dimensional analysis of the foot bones using bi-plane X-ray video and CT
  • A Hierarchical Feature Constraint to CamouflageMedical Adversarial Attacks
  • A Location Constrained Dual-branch Network for Reliable Diagnosis of Jaw Tumors and Cysts
  • A Spatial Guided Self-supervised Clustering Network for Medical Image Segmentation
  • AnaXNet: Anatomy Aware Multi-label Finding Classification in Chest X-ray
  • Attention-based Multi-scale Gated Recurrent Encoder with Novel Correlation Loss for COVID-19 Progression Prediction
  • Automatic Severity Rating for Improved Psoriasis Treatment
  • Beyond Non-Maximum Suppression - Detecting Lesions in Digital Breast Tomosynthesis Volumes
  • BSDA-Net: A Boundary Shape and Distance Aware Joint Learning Framework for Segmenting and Classifying OCTA Images
  • Chest Radiograph Disentanglement for COVID-19 Outcome Prediction
  • Colorectal Polyp Classification from White-light Colonoscopy Images via Domain Alignment
  • Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images
  • Cross-domain Depth Estimation Network for 3D Vessel Reconstruction in OCT Angiography
  • DeepOPG: Improving Orthopantomogram Finding Summarization with Weak Supervision
  • Distinguishing Differences Matters: Focal Contrastive Network for Peripheral Anterior Synechiae Recognition
  • DLLNet: An Attention-based Deep Learning Method for Dental Landmark Localization on High-Resolution 3D Digital Dental Models
  • EndoUDA: A modality independent segmentation approach for endoscopy imaging
  • High-particle simulation of Monte-Carlo dose distribution with 3D ConvLSTMs
  • HRENet: A Hard Region Enhancement Network for Polyp Segmentation
  • Interpretable gender classification from retinal fundus images using BagNets
  • I-SECRET: Importance-guided fundus image enhancement via semi-supervised contrastive constraining
  • Learning More for Free - A Multi Task Learning Approach for Improved Pathology Classification in Capsule Endoscopy
  • LIFE: A Generalizable Autodidactic Pipeline for 3D OCT-A Vessel Segmentation
  • Linear Prediction Residual for Efficient Diagnosis of Parkinson's Disease from Gait
  • MG-NET: Leveraging Pseudo-Imaging for Multi-Modal Metagenome Analysis
  • Multi-view analysis of unregistered medical images using cross-view transformers
  • Non-parametric vignetting correction for sparse spatial transcriptomics images
  • One-Shot Medical Landmark Detection
  • Order-Guided Disentangled Representation Learning for Ulcerative Colitis Classification with Limited Labels
  • OXnet: Deep Omni-supervised Thoracic Disease Detection from Chest X-rays
  • Perceptual Quality Assessment of Chest Radiograph
  • Pristine annotations-based multi-modal trained artificial intelligence solution to triage chest X-Ray for COVID19
  • Projective Skip-Connections for Segmentation Along a Subset of Dimensions in Retinal OCT
  • Radiomics-informed Deep Curriculum Learning for Breast Cancer Diagnosis
  • RATCHET: Medical Transformer for Chest X-ray Diagnosis and Reporting
  • Revisiting contour-driven and knowledge-based deformable models: application to 2D-3D proximal femur reconstruction from X-ray images
  • Self-Supervised Multi-Modal Alignment For Whole Body Medical Imaging
  • Semi-Supervised Learning for Bone Mineral Density Estimation in Hip X-ray Images
  • Sequential Gaussian Process Regression for Simultaneous Pathology Detection and Shape Reconstruction
  • Source-Free Domain Adaptive Fundus Image Segmentation with Denoised Pseudo-Labeling
  • Synthesis of Contrast-enhanced Spectral Mammograms from Low-energy Mammograms Using cGAN-Based Synthesis Network
  • Triplet-Branch Network with Prior-Knowledge Embedding for Fatigue Fracture Grading
  • You Only Learn Once: Universal Anatomical Landmark Detection

    • Outcome/disease prediction

  • 2.5D Thermometry Maps for MRI-guided Tumor Ablation
  • A Matrix Auto-encoder Framework to Align the Functional and Structural Connectivity Manifolds as Guided by Behavioral Phenotypes
  • A Structural Causal Model MR Images of Multiple Sclerosis
  • AMINN: Autoencoder-based Multiple Instance Neural Network Improves Outcome Prediction of Multifocal Liver Metastases
  • An Interpretable Approach to Automated Severity Scoring in Pelvic Trauma
  • AnaXNet: Anatomy Aware Multi-label Finding Classification in Chest X-ray
  • Attention based CNN-LSTM Network for Pulmonary Embolism Prediction on Chest Computed Tomography Pulmonary Angiograms
  • Attention-based Multi-scale Gated Recurrent Encoder with Novel Correlation Loss for COVID-19 Progression Prediction
  • Beyond Non-Maximum Suppression - Detecting Lesions in Digital Breast Tomosynthesis Volumes
  • BSDA-Net: A Boundary Shape and Distance Aware Joint Learning Framework for Segmenting and Classifying OCTA Images
  • CA-Net: Leveraging Contextual Features for Lung Cancer Prediction
  • Categorical Relation-Preserving Contrastive Knowledge Distillation for Medical Image Classification
  • Cells are Actors: Social Network Analysis with Classical ML for SOTA Histology Image Classification
  • Chest Radiograph Disentanglement for COVID-19 Outcome Prediction
  • Co-Graph Attention Reasoning based Imaging and Clinical Features Integration for Lymph Node Metastasis Prediction
  • Colorectal Polyp Classification from White-light Colonoscopy Images via Domain Alignment
  • Combining Attention-based Multiple Instance Learning and Gaussian Processes for CT Hemorrhage Detection
  • Controllable cardiac synthesis via disentangled anatomy arithmetic
  • Deep Orthogonal Fusion: Multimodal Prognostic Biomarker Discovery Integrating Radiology, Pathology, Genomic, and Clinical Data
  • Detecting Brain State Changes by Geometric Deep Learning of Functional Dynamics on Riemannian Manifold
  • Distinguishing Differences Matters: Focal Contrastive Network for Peripheral Anterior Synechiae Recognition
  • Do we need complex image features to personalize treatment of patients with locally advanced rectal cancer?
  • EMA: Auditing Data Removal from Trained Models
  • Facial and cochlear nerves characterization using deep reinforcement learning for landmark detection
  • Federated Contrastive Learning for Decentralized Unlabeled Medical Images
  • GKD: Semi-supervised Graph Knowledge Distillation for Graph-Independent Inference
  • GQ-GCN: Group Quadratic Graph Convolutional Network for Classification of Histopathological Images
  • Hierarchical graph pathomic network for progression free survival prediction
  • Hybrid Aggregation Network for Survival Analysis from Whole Slide Histopathological Images
  • Integration of Patch Features through Self-Supervised Learning and Transformer for Survival Analysis on Whole Slide Images
  • Intracerebral Haemorrhage Growth Prediction Based on Displacement Vector Field and Clinical Metadata
  • LensID: A CNN-RNN-Based Framework Towards Lens Irregularity Detection in Cataract Surgery Videos
  • Linear Prediction Residual for Efficient Diagnosis of Parkinson's Disease from Gait
  • Local-global Dual Perception based Deep Multiple Instance Learning for Retinal Disease Classification
  • Longitudinal self-supervision to disentangle inter-patient variability from disease progression
  • LuMiRa: An Integrated Lung Deformation Atlas and 3D-CNN model of Infiltrates for COVID-19 Prognosis
  • Lung Cancer Risk Estimation with Incomplete Data: A Joint Missing Imputation Perspective
  • MetaCon: Meta Contrastive Learning for Microsatellite Instability Detection
  • Multiple Instance Learning with Auxiliary Task Weighting for Multiple Myeloma Classification
  • Neighbor Matching for Semi-supervised Learning
  • Pancreas CT Segmentation by Predictive Phenotyping
  • Predicting Esophageal Fistula Risks Using a Multimodal Self-Attention Network
  • Predicting Symptoms from Multiphasic MRI via Multi-Instance Attention Learning for Hepatocellular Carcinoma Grading
  • Projection-wise Disentangling for Fair and Interpretable Representation Learning: Application to 3D Facial Shape Analysis
  • Sequential Gaussian Process Regression for Simultaneous Pathology Detection and Shape Reconstruction
  • Sequential Learning on Liver Tumor Boundary Semantics and Prognostic Biomarker Mining
  • SPARTA: An Integrated Stability, Discriminability, and Sparsity based Radiomic Feature Selection Approach
  • Spatial Attention-based Deep Learning System for Breast Cancer Pathological Complete Response Prediction with Serial Histopathology Images in Multiple Stains
  • Survival Prediction Based on Histopathology Imaging and Clinical Data: A Novel, Whole Slide CNN Approach
  • Tensor-based Multi-index Representation Learning for Major Depression Disorder Detection with Resting-state fMRI
  • Transfer Learning of Deep Spatiotemporal Networks to Model Arbitrarily Long Videos of Seizures
  • VinDr-SpineXR: A deep learning framework for spinal lesions detection and classification from radiographs
  • Whole Slide Images are 2D Point Clouds: Context-Aware Survival Prediction using Patch-based Graph Convolutional Networks

    • Population Imaging and Imaging Genetics

  • A Novel Bayesian Semi-parametric Model for Learning Heritable Imaging Traits
  • Image-derived phenotype extraction for genetic discovery via unsupervised deep learning in CMR images
  • Projection-wise Disentangling for Fair and Interpretable Representation Learning: Application to 3D Facial Shape Analysis

    • Surgical Data Science

  • Acoustic-based Spatio-temporal Learning for Press-fit Evaluation of Femoral Stem Implants
  • CataNet: Predicting remaining cataract surgery duration
  • Detection of critical structures in laparoscopic cholecystectomy using label relaxation and self-supervision
  • E-DSSR: Efficient Dynamic Surgical Scene Reconstruction with Transformer-based Stereoscopic Depth Perception
  • Effective semantic segmentation in Cataract surgery: What matters most?
  • Multi-View Surgical Video Action Detection via Mixed Global View Attention
  • SurgeonAssist-Net: Towards Context-Aware Head-Mounted Display-Based Augmented Reality for Surgical Guidance
  • Surgical Instruction Generation with Transformers
  • Surgical Workflow Anticipation using Instrument Interaction
  • Task Fingerprinting for Meta Learning in Biomedical Image Analysis

    • Surgical Planning and Simulation

  • 3D Brain Midline Delineation for Hematoma Patients
  • A new Approach to Orthopedic Surgery Planning using Deep Reinforcement Learning and Simulation
  • A self-supervised deep framework for reference bony shape estimation in orthognathic surgical planning
  • Acoustic-based Spatio-temporal Learning for Press-fit Evaluation of Femoral Stem Implants
  • Automatic Path Planning for Safe Guide Pin Insertion in PCL Reconstruction Surgery
  • Content-Preserving Unpaired Translation from Simulated to Realistic Ultrasound Images
  • Deep Simulation of Facial Appearance Changes Following Craniomaxillofacial Bony Movements in Orthognathic Surgical Planning
  • DLLNet: An Attention-based Deep Learning Method for Dental Landmark Localization on High-Resolution 3D Digital Dental Models
  • EMDQ-SLAM: Real-time High-resolution Reconstruction of Soft Tissue Surface from Stereo Laparoscopy Videos
  • Facial and cochlear nerves characterization using deep reinforcement learning for landmark detection
  • Improving hexahedral-FEM-based plasticity in surgery simulation
  • Intra-operative Update of Boundary Conditions for Patient-specific Surgical Simulation
  • Multi-View Surgical Video Action Detection via Mixed Global View Attention
  • Patient-specific virtual spine straightening and vertebra inpainting: An automatic framework for osteoplasty planning
  • Rapid treatment planning for low-dose-rate prostate brachytherapy with TP-GAN
  • Revisiting contour-driven and knowledge-based deformable models: application to 2D-3D proximal femur reconstruction from X-ray images
  • Surgical Workflow Anticipation using Instrument Interaction
  • Using Multiple Images and Contours for Deformable 3D-2D Registration of a Preoperative CT in Laparoscopic Liver Surgery
  • Whole Heart Mesh Generation For Image-Based Computational Simulations By Learning Free-From Deformations

    • Surgical Skill and Work Flow Analysis

  • Acoustic-based Spatio-temporal Learning for Press-fit Evaluation of Femoral Stem Implants
  • CataNet: Predicting remaining cataract surgery duration
  • Class-Incremental Domain Adaptation with Smoothing and Calibration for Surgical Report Generation
  • Effective semantic segmentation in Cataract surgery: What matters most?
  • Efficient Global-Local Memory for Real-time Instrument Segmentation of Robotic Surgical Video
  • Interhemispheric functional connectivity in the primary motor cortex distinguishes between training on a physical and a virtual surgical simulator
  • Multi-View Surgical Video Action Detection via Mixed Global View Attention
  • OperA: Attention-Regularized Transformers for Surgical Phase Recognition
  • SurgeonAssist-Net: Towards Context-Aware Head-Mounted Display-Based Augmented Reality for Surgical Guidance
  • Surgical Workflow Anticipation using Instrument Interaction
  • Trans-SVNet: Accurate Phase Recognition from Surgical Videos via Hybrid Embedding Aggregation Transformer

    • Surgical Visualization and Mixed, Augmented and Virtual Reality

  • 3D Semantic Mapping from Arthroscopy using Out-of-distribution Pose and Depth and In-distribution Segmentation Training
  • Acoustic-based Spatio-temporal Learning for Press-fit Evaluation of Femoral Stem Implants
  • Content-Preserving Unpaired Translation from Simulated to Realistic Ultrasound Images
  • EMDQ-SLAM: Real-time High-resolution Reconstruction of Soft Tissue Surface from Stereo Laparoscopy Videos
  • FoldIt: Haustral Folds Detection and Segmentation in Colonoscopy Videos
  • hSDB-instrument: Instrument Localization Database for Laparoscopic and Robotic Surgeries
  • Image-based Incision Detection for Topological Intraoperative 3D Model Update in Augmented Reality Assisted Laparoscopic Surgery
  • Improving hexahedral-FEM-based plasticity in surgery simulation
  • Interhemispheric functional connectivity in the primary motor cortex distinguishes between training on a physical and a virtual surgical simulator
  • Prototypical Interaction Graph for Unsupervised Domain Adaptation in Surgical Instrument Segmentation
  • Quantitative Assessments for Ultrasound Probe Calibration
  • SurgeonAssist-Net: Towards Context-Aware Head-Mounted Display-Based Augmented Reality for Surgical Guidance
  • Using Multiple Images and Contours for Deformable 3D-2D Registration of a Preoperative CT in Laparoscopic Liver Surgery

    • Visualisation in Biomedical Imaging

  • A Principled Approach to Failure Analysis and Model Repairment: Demonstration in Medical Imaging
  • Cross-domain Depth Estimation Network for 3D Vessel Reconstruction in OCT Angiography
  • Facial and cochlear nerves characterization using deep reinforcement learning for landmark detection
  • Focusing on Clinically Interpretable Features: Selective Attention Regularization for Liver Biopsy Image Classification
  • FoldIt: Haustral Folds Detection and Segmentation in Colonoscopy Videos
  • High-particle simulation of Monte-Carlo dose distribution with 3D ConvLSTMs
  • Interhemispheric functional connectivity in the primary motor cortex distinguishes between training on a physical and a virtual surgical simulator
  • Interpretable gender classification from retinal fundus images using BagNets
  • Learned super resolution ultrasound for improved breast lesion characterization
  • Learning Neuron Stitching for Connectomics
  • LensID: A CNN-RNN-Based Framework Towards Lens Irregularity Detection in Cataract Surgery Videos
  • Multi-StyleGAN: Towards Image-Based Simulation of Time-Lapse Live-Cell Microscopy
  • Multi-Task, Multi-Domain Deep Segmentation with Shared Representations and Contrastive Regularization for Sparse Pediatric Datasets
  • Pay Attention with Focus: A Novel Learning Scheme for Classification of Whole Slide Images
  • Perceptual Quality Assessment of Chest Radiograph
  • Phase-independent Latent Representation for Cardiac Shape Analysis
  • Sequential Gaussian Process Regression for Simultaneous Pathology Detection and Shape Reconstruction
  • Study Group Learning: Improving Retinal Vessel Segmentation Trained with Noisy Labels
  • Using Multiple Images and Contours for Deformable 3D-2D Registration of a Preoperative CT in Laparoscopic Liver Surgery
  • Whole Heart Mesh Generation For Image-Based Computational Simulations By Learning Free-From Deformations