List of Papers

• 2.5D Thermometry Maps for MRI-guided Tumor Ablation

• 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 Semantic Mapping from Arthroscopy using Out-of-distribution Pose and Depth and In-distribution Segmentation Training

• 3D Transformer-GAN for High-quality PET Reconstruction

• 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 Coherent Cooperative Learning Framework Based on Transfer Learning for Unsupervised Cross-domain Classification

• A computational geometry approach for modeling neuronal fiber pathways

• A Data-driven Approach for High Frame Rate Synthetic Transmit Aperture Ultrasound Imaging

• A Deep Discontinuity-Preserving Image Registration Network

• A Deep Learning Bidirectional Temporal Tracking Algorithm for Automated Blood Cell Counting from Non-invasive Capillaroscopy Videos

• A Deep Network for Joint Registration and Parcellation of Cortical Surfaces

• A Deep Reinforced Tree-traversal Agent for Coronary Artery Centerline Extraction

• A Hierarchical Feature Constraint to CamouflageMedical Adversarial Attacks

• 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 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 Multi-Branch Hybrid Transformer Network for Corneal Endothelial Cell Segmentation

• A Neural Framework for Multi-Variable Lesion Quantification Through B-mode Style Transfer

• A new Approach to Orthopedic Surgery Planning using Deep Reinforcement Learning and Simulation

• A Novel Bayesian Semi-parametric Model for Learning Heritable Imaging Traits

• A Novel Hybrid Convolutional Neural Network for Accurate Organ Segmentation in 3D Head and Neck CT Images

• A Principled Approach to Failure Analysis and Model Repairment: Demonstration in Medical Imaging

• 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

• A Spatial Guided Self-supervised Clustering Network for Medical Image Segmentation

• A spherical convolutional neural network for white matter structure imaging via diffusion MRI

• A Structural Causal Model MR Images of Multiple Sclerosis

• A Topological-Attention ConvLSTM Network and Its Application to EM Images

• A Unified Hyper-GAN Model for Unpaired Multi-contrast MR Image Translation

• Acceleration by deep-learnt sharing of superfluous information in multi-contrast MRI

• Accounting for Dependencies in Deep Learning based Multiple Instance Learning for Whole Slide Imaging

• Accurate parameter estimation in fetal diffusion-weighted MRI - learning from fetal and newborn data

• ACN: Adversarial Co-training Network for Brain Tumor Segmentation with Missing Modalities

• Acoustic-based Spatio-temporal Learning for Press-fit Evaluation of Femoral Stem Implants

• 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

• Adversarial Domain Feature Adaptation for Bronchoscopic Depth Estimation

• Adversarial learning of cancer tissue representations

• Airway Anomaly Detection by Graph Neural Network

• AlignTransformer: Hierarchical Alignment of Visual Regions and Disease Tags for Medical Report Generation

• 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

• Anatomy of Domain Shift Impact on U-Net Layers in MRI Segmentation

• Anatomy-Constrained Contrastive Learning for Synthetic Segmentation without Ground-truth

• AnaXNet: Anatomy Aware Multi-label Finding Classification in Chest X-ray

• Annotation-efficient Cell Counting

• 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

• AtrialGeneral: Domain Generalization for Left Atrial Segmentation of Multi-Center LGE MRIs

• 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

• Automatic Path Planning for Safe Guide Pin Insertion in PCL Reconstruction Surgery

• Automatic Polyp Segmentation via Multi-scale Subtraction Network

• Automatic Severity Rating for Improved Psoriasis Treatment

• Automating Embryo Development Stage Detection in Time-Lapse Imaging with Synergic Loss and Temporal Learning

• AxonEM Dataset: 3D Axon Instance Segmentation of Brain Cortical Regions

• Balanced-MixUp for highly imbalanced medical image classification

• Bayesian Atlas Building with Hierarchical Priors for Subject-specific Regularization

• Beyond COVID-19 Diagnosis: Prognosis with Hierarchical Graph Representation Learning

• Beyond Non-Maximum Suppression - Detecting Lesions in Digital Breast Tomosynthesis Volumes

• BI-RADS Classification of Calcification on Mammograms

• 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

• Building Dynamic Hierarchical Brain Networks and Capturing Transient Meta-states for Early Mild Cognitive Impairment Diagnosis

• CA^{2.5}-Net Nuclei Segmentation Framework with a Microscopy Cell Benchmark Collection

• CA-Net: Leveraging Contextual Features for Lung Cancer Prediction

• Cardiac Transmembrane Potential Imaging with GCN Based Iterative Soft Threshold Network

• C-arm positioning for spinal standard projections in different intra-operative settings

• CarveMix: A Simple Data Augmentation Method for Brain Lesion Segmentation

• CataNet: Predicting remaining cataract surgery duration

• Categorical Relation-Preserving Contrastive Knowledge Distillation for Medical Image Classification

• CCBANet: Cascading Context and Balancing Attention for Polyp Segmentation

• Cell Detection from Imperfect Annotation by Pseudo Label Selection Using P-classification

• Cell Detection in Domain Shift Problem Using Pseudo-Cell-Position Heatmap

• Cells are Actors: Social Network Analysis with Classical ML for SOTA Histology Image Classification

• Chest Radiograph Disentanglement for COVID-19 Outcome Prediction

• Class-Incremental Domain Adaptation with Smoothing and Calibration for Surgical Report Generation

• Coarse-to-fine Segmentation of Organs at Risk in Nasopharyngeal Carcinoma Radiotherapy

• Co-Generation and Segmentation for Generalized Surgical Instrument Segmentation on Unlabelled Data

• 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 Deformable Image Registration with Convolutional Neural Network

• 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

• Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images

• Construction of Longitudinally Consistent 4D Infant Cerebellum Atlases based on Deep Learning

• Content-Preserving Unpaired Translation from Simulated to Realistic Ultrasound Images

• Context-aware virtual adversarial training for anatomically-plausible segmenation

• Continual Learning with Bayesian Model based on a Fixed Pre-trained Feature Extractor

• Continuous-Time Deep Glioma Growth Models

• 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

• 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

• Cost-Sensitive Meta-Learning for Progress Prediction of Subjective Cognitive Decline with Brain Structural MRI

• CoTr: Efficiently Bridging CNN and Transformer for 3D Medical Image Segmentation

• Covariate Correcting Networks for Identifying Associations between Socioeconomic Factors and Brain Outcomes in Children

• CPNet: Cycle Prototype Network for Weakly-supervised 3D Renal Chamber Segmentation

• Cross-domain Depth Estimation Network for 3D Vessel Reconstruction in OCT Angiography

• Cross-modal Attention for MRI and Ultrasound Volume Registration

• Culprit-Prune-Net: Efficient Continual Sequential Multi-Domain Learning with Application to Skin Lesion Classification

• DAE-GCN: Identifying Disease-Related Features for Disease Prediction

• Data Augmentation in Logit Space for Medical Image Classification with Limited Training Data

• Data-driven mapping between functional connectomes using optimal transport

• DA-VSR: Domain Adaptable Volumetric Super-Resolution For Medical Images

• 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 Iterative 2D/3D Registration

• Deep J-Sense: Accelerated MRI Reconstruction via Unrolled Alternating Optimization

• Deep Neural Dynamic Bayesian Networks applied to EEG sleep spindles modeling

• Deep Open Snake Tracker for Vessel Tracing

• Deep Orthogonal Fusion: Multimodal Prognostic Biomarker Discovery Integrating Radiology, Pathology, Genomic, and Clinical Data

• Deep Reinforcement Exemplar Learning for Annotation Refinement

• Deep Simulation of Facial Appearance Changes Following Craniomaxillofacial Bony Movements in Orthognathic Surgical Planning

• 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

• Deformed2Self: Self-Supervised Denoising for Dynamic Medical Imaging

• Demystifying T1-MRI to FDG18-PET Image Translation via Representational Similarity

• Depth Estimation for Colonoscopy Images with Self-supervised Learning from Videos

• Detecting Brain State Changes by Geometric Deep Learning of Functional Dynamics on Riemannian Manifold

• Detecting Hypo-plastic Left Heart Syndrome in Fetal Ultrasound via Disease-specific Atlas Maps

• Detecting Outliers with Poisson Image Interpolation

• 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

• Determination of error in 3D CT to 2D fluoroscopy image registration for endobronchial guidance

• Developmental Stage Classification of Embryos Using Two-Stream Neural Network with Linear-Chain Conditional Random Field

• Disentangled and Proportional Representation Learning for Multi-View Brain Connectomes

• Disentangled Sequential Graph Autoencoder for Preclinical Alzheimer's Disease Characterizations from ADNI Study

• Distilling effective supervision for robust medical image segmentation with noisy labels

• Distinguishing Differences Matters: Focal Contrastive Network for Peripheral Anterior Synechiae Recognition

• Distortion Energy for Deep Learning-based Volumetric Finite Element Mesh Generation for Aortic Valves

• DLLNet: An Attention-based Deep Learning Method for Dental Landmark Localization on High-Resolution 3D Digital Dental Models

• Do we need complex image features to personalize treatment of patients with locally advanced rectal cancer?

• Domain Composition and Attention for Unseen-Domain Generalizable Medical Image Segmentation

• Domain Generalization for Mammography Detection via Multi-style and Multi-view Contrastive Learning

• DT-MIL: Deformable Transformer for Multi-instance Learning on Histopathological Image

• 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

• Duo-SegNet: Adversarial Dual-Views for Semi-Supervised Medical Image Segmentation

• Early Detection of Liver Fibrosis Using Graph Convolutional Networks

• EchoCP: An Echocardiography Dataset in Contrast Transthoracic Echocardiography for Patent Foramen Ovale Diagnosis

• E-DSSR: Efficient Dynamic Surgical Scene Reconstruction with Transformer-based Stereoscopic Depth Perception

• Effective Pancreatic Cancer Screening on Non-contrast CT Scans via Anatomy-Aware Transformers

• 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 Global-Local Memory for Real-time Instrument Segmentation of Robotic Surgical Video

• Efficient neural network approximation of robust PCA for automated analysis of calcium imaging data

• 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

• EMA: Auditing Data Removal from Trained Models

• EMDQ-SLAM: Real-time High-resolution Reconstruction of Soft Tissue Surface from Stereo Laparoscopy Videos

• EndoUDA: A modality independent segmentation approach for endoscopy imaging

• End-to-end Ugly Duckling Sign Detection for Melanoma Identification with Transformers

• End-to-end Ultrasound Frame to Volume Registration

• Energy-Based Supervised Hashing for Multimorbidity Image Retrieval

• Enhanced Breast Lesion Classification via Knowledge Guided Cross-Modal and Semantic Data Augmentation

• Equivariant Filters for Efficient Tracking in 3D Imaging

• Estimation of High Frame Rate Digital Subtraction Angiography Sequences at Low Radiation Dose

• Estimation of spontaneous neuronal activity using homomorphic filtering

• 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

• 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

• Fast Magnetic Resonance Imaging on Regions of Interest: From Sensing to Reconstruction

• Federated Contrastive Learning for Decentralized Unlabeled Medical Images

• Federated Contrastive Learning for Volumetric Medical Image Segmentation

• Federated Semi-supervised Medical Image Classification via Inter-client Relation Matching

• Federated Whole Prostate Segmentation in MRI with Personalized Neural Architectures

• 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

• Few-shot Transfer Learning for Hereditary Retinal Diseases Recognition

• Fighting Class Imbalance with Contrastive Learning

• Flip Learning: Erase to Segment

• Focusing on Clinically Interpretable Features: Selective Attention Regularization for Liver Biopsy Image Classification

• FoldIt: Haustral Folds Detection and Segmentation in Colonoscopy Videos

• From Brain to Body: Learning Low-Frequency Respiration and Cardiac Signals from fMRI Dynamics

• From Pixel to Whole Slide: Automatic Detection of Microvascular Invasion in Hepatocellular Carcinoma on Histopathological Image via Cascaded Networks

• Fully Test-time Adaptation for Image Segmentation

• Functional Magnetic Resonance Imaging data augmentation through conditional ICA

• Generalised Super Resolution for Quantitative MRI Using Self-Supervised Mixture of Experts

• 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

• Generator Versus Segmentor: Pseudo-healthy Synthesis

• GKD: Semi-supervised Graph Knowledge Distillation for Graph-Independent Inference

• 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

• Graph Transformers for Characterization and Interpretation of Surgical Margins

• Group Shift Pointwise Convolution for Volumetric Medical Image Segmentation

• Harmonization with Flow-based Causal Inference

• 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 graph pathomic network for progression free survival prediction

• Hierarchical Phenotyping and Graph Modeling of Spatial Architecture in Lymphoid Neoplasms

• 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

• High-particle simulation of Monte-Carlo dose distribution with 3D ConvLSTMs

• High-Resolution Hierarchical Adversarial Learning for OCT Speckle Noise Reduction

• High-resolution segmentation of lumbar vertebrae from conventional thick slice MRI

• HRENet: A Hard Region Enhancement Network for Polyp Segmentation

• hSDB-instrument: Instrument Localization Database for Laparoscopic and Robotic Surgeries

• Hybrid Aggregation Network for Survival Analysis from Whole Slide Histopathological Images

• Hybrid graph convolutional neural networks for anatomical segmentation

• Hybrid Supervision Learning for Whole Slide Image Classification

• Identifying Quantitative and Explanatory Tumor Indexes from Dynamic Contrast Enhanced Ultrasound

• Image-based Incision Detection for Topological Intraoperative 3D Model Update in Augmented Reality Assisted Laparoscopic Surgery

• Image-derived phenotype extraction for genetic discovery via unsupervised deep learning in CMR images

• Image-to-Graph Convolutional Network for Deformable Shape Reconstruction from a Single Projection Image

• 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

• Improved Brain Lesion Segmentation with Anatomical Priors from Healthy Subjects

• Improving Generalizability in Limited-Angle CT Reconstruction with Sinogram Extrapolation

• Improving hexahedral-FEM-based plasticity in surgery simulation

• Improving Pneumonia Localization via Cross-Attention on Medical Images and Reports

• Improving the Explainability of Skin Cancer Diagnosis Using CBIR

• Incorporating Isodose Lines and Gradient Information via Multi-task Learning for Dose Prediction in Radiotherapy

• Increasing Consistency of Evoked Response in Thalamic Nuclei During Repetitive Burst Stimulation of Peripheral Nerve in Humans

• InDuDoNet: An Interpretable Dual Domain Network for CT Metal Artifact Reduction

• 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

• Inter Extreme Points Geodesics for End-to-End Weakly Supervised Image Segmentation

• Interactive segmentation via deep learning and B-spline explicit active surfaces

• Interactive smoothing parameter optimization in DBT Reconstruction using Deep learning

• Interhemispheric functional connectivity in the primary motor cortex distinguishes between training on a physical and a virtual surgical simulator

• Interpretable deep learning for multimodal super-resolution of medical images

• Interpretable gender classification from retinal fundus images using BagNets

• Inter-Regional High-level Relation Learning from Functional Connectivity via Self-Supervision

• Intracerebral Haemorrhage Growth Prediction Based on Displacement Vector Field and Clinical Metadata

• Intra-operative Update of Boundary Conditions for Patient-specific Surgical Simulation

• IREM: High-Resolution Magnetic Resonance Image Reconstruction via Implicit Neural Representation

• I-SECRET: Importance-guided fundus image enhancement via semi-supervised contrastive constraining

• Joint Motion Correction and Super Resolution for Cardiac Segmentation via Latent Optimisation

• Joint Optimization of Hadamard Sensing and Reconstruction in Compressed Sensing Fluorescence Microscopy

• 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

• kCBAC-Net: Deeply Supervised Complete Bipartite Networks with Asymmetric Convolutions for Medical 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

• LambdaUNet: 2.5D Stroke Lesion Segmentation of Diffusion-weighted MR Images

• LDPolypVideo Benchmark: A Large-scale Colonoscopy Video Dataset of Diverse Polyps

• Learnable Multi-scale Fourier Interpolation for Sparse View CT Image Reconstruction

• Learnable Oriented-Derivative Network for Polyp Segmentation

• Learned super resolution ultrasound for improved breast lesion characterization

• Learning 4D Infant Cortical Surface Atlas with Unsupervised Spherical Networks

• Learning Consistency- and Discrepancy-Context for 2D Organ Segmentation

• Learning Dual Transformer Network for Diffeomorphic Registration

• 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 Neuron Stitching for Connectomics

• Learning Spatiotemporal Probabilistic Atlas of Fetal Brains with Anatomically Constrained Registration Network

• Learning to Address Intra-segment Misclassification in Retinal Imaging

• Learning to Predict Error for MRI Reconstruction

• Learning Unsupervised Parameter-specific Affine Transformation for Medical Images Registration

• 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

• Learning-based attenuation quantification in abdominal ultrasound

• 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

• Lesion-based Contrastive Learning for Diabetic Retinopathy Grading from Fundus Images

• Leveraging Auxiliary Information from EMR for Weakly Supervised Pulmonary Nodule Detection

• LG-Net: Lesion Gate Network for Multiple Sclerosis Lesion Inpainting

• LIFE: A Generalizable Autodidactic Pipeline for 3D OCT-A Vessel Segmentation

• Linear Prediction Residual for Efficient Diagnosis of Parkinson's Disease from Gait

• Local Morphological Measures Confirm that Folding within Small Partitions of the Human Cortex Follows Universal Scaling Law

• Local-global Dual Perception based Deep Multiple Instance Learning for Retinal Disease Classification

• Longitudinal Correlation Analysis for Decoding Multi-Modal Brain Development

• Longitudinal Quantitative Assessment of COVID-19 Infection Progression from Chest CTs

• 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

• MASC-Units: Training Oriented Filters for Segmenting Curvilinear Structures

• MBFF-Net: Multi-Branch Feature Fusion Network for Carotid Plaque Segmentation in Ultrasound

• Medical Image Registration Based on Uncoupled Learning and Accumulative Enhancement

• Medical Matting: A New Perspective on Medical Segmentation with Uncertainty

• Medical Transformer: Gated Axial-Attention for Medical Image Segmentation

• Memory-efficient Learning for High-dimensional MRI Reconstruction

• MetaCon: Meta Contrastive Learning for Microsatellite Instability Detection

• 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

• MIL-VT: Multiple Instance Learning Enhanced Vision Transformer for Fundus Image Classification

• Modality Completion via Gaussian Process Prior Variational Autoencoders for Multi-Modal Glioma Segmentation

• Modality-aware Mutual Learning for Multi-modal Medical Image Segmentation

• MorphSet: Improving Renal Histopathology Case Assessment Through Learned Prognostic Vectors

• Motion Correction for Liver DCE-MRI with Time-Intensity Curve Constraint

• MouseGAN: GAN-Based Multiple MRI Modalities Synthesis and Segmentation for Mouse Brain Structures

• MRI Super-Resolution Through Generative Degradation Learning

• 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-Contrast MRI Super-Resolution via a Multi-Stage Integration Network

• Multi-frame Attention Network for Left Ventricle Segmentation in 3D Echocardiography

• 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

• Multi-level Relationship Capture Network for Automated Skin Lesion Recognition

• Multimodal MRI Acceleration via Deep Cascading Networks with Peer-layer-wise Dense Connections

• 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

• Multimodal Sensing Guidewire for C-arm Navigation with Random UV Enhanced Optical Sensors using Spatio-temporal Networks

• Multi-phase Liver Tumor Segmentation with Spatial Aggregation and Uncertain Region Inpainting

• Multiple Instance Learning with Auxiliary Task Weighting for Multiple Myeloma Classification

• Multiple Meta-model Quantifying for Medical Visual Question Answering

• Multi-scale Neural ODEs for 3D Medical Image Registration

• Multi-site Incremental Image Quality Assessment of Structural MRI via Consensus Adversarial Representation Adaptation

• 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

• Multi-view analysis of unregistered medical images using cross-view transformers

• Multi-View Surgical Video Action Detection via Mixed Global View Attention

• Neighbor Matching for Semi-supervised Learning

• Nesterov Accelerated ADMM for Fast Diffeomorphic Image Registration

• nnDetection: A Self-configuring Method for Medical Object Detection

• Noise Mapping and Removal in Complex-Valued Multi-Channel MRI via Optimal Shrinkage of Singular Values

• 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

• 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

• NucMM Dataset: 3D Neuronal Nuclei Instance Segmentation at Sub-Cubic Millimeter Scale

• Observational Supervision for Medical Image Classification using Gaze Data

• OLVA: Optimal Latent Vector Alignment for Unsupervised Domain Adaptation in Medical Image Segmentation

• On the relationship between calibrated predictors and unbiased volume estimation

• One-Shot Medical Landmark Detection

• OperA: Attention-Regularized Transformers for Surgical Phase Recognition

• Order-Guided Disentangled Representation Learning for Ulcerative Colitis Classification with Limited Labels

• Orthogonal Ensemble Networks for Biomedical Image Segmentation

• Over-and-Under Complete Convolutional RNN for MRI Reconstruction

• OXnet: Deep Omni-supervised Thoracic Disease Detection from Chest X-rays

• PAC Bayesian Performance Guarantees for (Stochastic) Deep Networks in Medical Imaging

• Pancreas CT Segmentation by Predictive Phenotyping

• Parallel Capsule Networks for Classification of White Blood Cells

• 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

• Pay Attention with Focus: A Novel Learning Scheme for Classification of Whole Slide Images

• Perceptual Quality Assessment of Chest Radiograph

• Personalized CT Organ Dose Estimation from Scout Images

• 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

• Personalized Retrogress-Resilient Framework for Real-World Medical Federated Learning

• Phase-independent Latent Representation for Cardiac Shape Analysis

• 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

• 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

• Pristine annotations-based multi-modal trained artificial intelligence solution to triage chest X-Ray for COVID19

• Progressively Normalized Self-Attention Network for Video Polyp Segmentation

• Projection-wise Disentangling for Fair and Interpretable Representation Learning: Application to 3D Facial Shape Analysis

• Projective Skip-Connections for Segmentation Along a Subset of Dimensions in Retinal OCT

• Prototypical Interaction Graph for Unsupervised Domain Adaptation in Surgical Instrument Segmentation

• Prototypical models for classifying high-risk atypical breast lesions

• Q-space Conditioned Translation Networks for Directional Synthesis of Diffusion Weighted Images from Multi-modal Structural MRI

• Quality-Aware Memory Network for Interactive Volumetric Image Segmentation

• Quantifying structural connectivity in brain tumor patients

• Quantitative Assessments for Ultrasound Probe Calibration

• Radiomics-informed Deep Curriculum Learning for Breast Cancer Diagnosis

• Ranking loss: A ranking-based deep neural network for colorectal cancer grading in pathology images

• Rapid treatment planning for low-dose-rate prostate brachytherapy with TP-GAN

• RATCHET: Medical Transformer for Chest X-ray Diagnosis and Reporting

• Real-Time Mapping of Tissue Properties for Magnetic Resonance Fingerprinting

• Real-Time Rotated Convolutional Descriptor for Surgical Environments

• Reciprocal Learning for Semi-supervised Segmentation

• Recurrent Multigraph Integrator Network for Predicting the Evolution of Population-Driven Brain Connectivity Templates

• Reference-Relation Guided Autoencoder with Deep CCA Restriction for Awake-to-Sleep Brain Functional Connectome Prediction

• Refined Local-imbalance-based Weight for Airway Segmentation in CT

• Region Ensemble Network for MCI Conversion Prediction With a Relation Regularized Loss

• Relational Subsets Knowledge Distillation for Long-tailed Retinal Diseases Recognition

• Renal Cell Carcinoma Classification from Vascular Morphology

• ReSGAN: Intracranial Hemorrhage Segmentation with Residuals of Synthetic Brain CT Scans

• Residual Feedback Network for Breast Lesion Segmentation in Ultrasound Image

• Rethinking Ultrasound Augmentation: A Physics-Inspired Approach

• Retina-Match: Ipsilateral Mammography Lesion Matching in a Single Shot Detection Pipeline

• Revisiting contour-driven and knowledge-based deformable models: application to 2D-3D proximal femur reconstruction from X-ray images

• Revisiting iterative highly efficient optimisation schemes in medical image registration

• RibSeg Dataset and Strong Point Cloud Baselines for Rib Segmentation from CT Scans

• Rician noise estimation for 3D Magnetic Resonance Images based on Benford's Law

• RLP-Net: Recursive Light Propagation Network for 3-D Virtual Refocusing

• 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

• SAME: Deformable Image Registration based on Self-supervised Anatomical Embeddings

• SAR: Scale-Aware Restoration Learning for 3D Tumor Segmentation

• Scalable joint detection and segmentation of surgical instruments with weak supervision

• Scalable, Axiomatic Explanations of Deep Alzheimer's Diagnosis from Heterogeneous Data

• Seg4Reg+: A Local and Global ConsistencyLearning between Spine Segmentation and CobbAngle Regression

• Segmentation of Left Atrial MR Images via Self-supervised Semi-supervised Meta-learning

• SegRecon: Learning Joint Brain Surface Reconstruction and Segmentation from Images

• Selective Learning from External Data for CT Image Segmentation

• Self Context and Shape Prior for Sensorless Freehand 3D Ultrasound Reconstruction

• Self-adversarial Learning for Detection of Clustered Microcalcifications in Mammograms

• 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

• Semantic Consistent Unsupervised Domain Adaptation for Cross-modality Medical Image Segmentation

• 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

• 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

• Shallow Attention Network for Polyp Segmentation

• Sharpening Local Interpretable Model-agnostic Explanations for Histopathology: Improved Understandability and Reliability

• SimTriplet: Simple Triplet Representation Learning with a Single GPU

• 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

• 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

• Spectral Embedding Approximation and Descriptor Learning for Craniofacial Volumetric Image Correspondence

• 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

• SSLP: Spatial Guided Self-supervised Learning on Pathological Images

• Stain Mix-up: Unsupervised Domain Generalization for Histopathology Images

• 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

• Structure-Preserving Multi-Domain Stain Color Augmentation using Style-Transfer with Disentangled Representations

• Study Group Learning: Improving Retinal Vessel Segmentation Trained with Noisy Labels

• Style Curriculum Learning for Robust Medical Image Segmentation

• Style Transfer Using Generative Adversarial Networks for Multi-Site MRI Harmonization

• Superpixel-guided Iterative Learning from Noisy Labels for Medical Image Segmentation

• Supervised Contrastive Pre-Training for Mammographic Triage Screening Models

• Surface-Guided Image Fusion for Preserving Cortical Details in Human Brain Templates

• 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

• Survival Prediction Based on Histopathology Imaging and Clinical Data: A Novel, Whole Slide CNN Approach

• Symmetry-Enhanced Attention Network for Acute Ischemic Infarct Segmentation with Non–Contrast CT Images

• 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

• TarGAN: Target-Aware Generative Adversarial Networks for Multi-modality Medical Image Translation

• Targeted Gradient Descent: A Novel Method for Convolutional Neural Networks Fine-tuning and Online-learning

• Task Fingerprinting for Meta Learning in Biomedical Image Analysis

• Task Transformer Network for Joint MRI Reconstruction and Super-Resolution

• Task-Oriented Low-Dose CT Image Denoising

• 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

• Text2Brain: Synthesis of Brain Activation Maps from Free-form Text Query

• 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 a non-invasive diagnosis of portal hypertension based on an Eulerian CFD model with diffuse boundary conditions

• Towards Efficient Human-Machine Collaboration: Real-Time Correction Effort Prediction for Ultrasound Data Acquisition

• Towards Robust Dual-view Transformation via Densifying Sparse Supervision for Mammography Lesion Matching

• Towards Robust General Medical Image Segmentation

• Towards Semantic Interpretation of Thoracic Disease and COVID-19 Diagnosis Models

• Towards Ultrafast MRI via Extreme k-Space Undersampling and Superresolution

• Trainable summarization to improve breast tomosynthesis classification

• Training Automatic View Planner for Cardiac MR Imaging via Self-Supervision by Spatial Relationship between Views

• Training Deep Networks for Prostate Cancer Diagnosis Using Coarse Histopathological Labels

• TransBTS: Multimodal Brain Tumor Segmentation Using Transformer

• TransCT: Dual-path Transformer for Low Dose Computed Tomography

• Transfer Learning of Deep Spatiotemporal Networks to Model Arbitrarily Long Videos of Seizures

• Transformer Network for Significant Stenosis Detection in CCTA of Coronary Arteries

• TransFuse: Fusing Transformers and CNNs for Medical Image Segmentation

• TransPath: Transformer-based Self-supervised Learning for Histopathological Image Classification

• Trans-SVNet: Accurate Phase Recognition from Surgical Videos via Hybrid Embedding Aggregation Transformer

• Tripled-uncertainty Guided Mean Teacher model for Semi-supervised Medical Image Segmentation

• Triplet-Branch Network with Prior-Knowledge Embedding for Fatigue Fracture Grading

• TumorCP: A Simple but Effective Object-Level Data Augmentation for Tumor Segmentation

• TUN-Det: A Novel Network for Thyroid Ultrasound Nodule Detection

• 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

• U-DuDoNet: Unpaired dual-domain network for CT metal artifact reduction

• Ultrasound Video Transformers for Cardiac Ejection Fraction Estimation

• Uncertainty Aware Deep Reinforcement Learning for Anatomical Landmark Detection in Medical Images

• Uncertainty-Aware Label Rectification for Domain Adaptive Mitochondria Segmentation

• Uncertainty-Guided Progressive GANs for Medical Image Translation

• Universal Undersampled MRI Reconstruction

• Unsupervised Contrastive Learning of Radiomics and Deep Features for Label-Efficient Tumor Classification

• Unsupervised Diffeomorphic Surface Registration and Non-Linear Modelling

• Unsupervised Domain Adaptation for Small Bowel Segmentation using Disentangled Representation

• Unsupervised Network Learning for Cell Segmentation

• 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

• 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

• Variational Topic Inference for Chest X-Ray Report Generation

• VertNet: Accurate Vertebra Localization and Identification Network from CT Images

• Vessel Width Estimation via Convolutional Regression

• VinDr-SpineXR: A deep learning framework for spinal lesions detection and classification from radiographs

• Visual-Assisted Probe Movement Guidance for Obstetric Ultrasound Scanning using Landmark Retrieval

• Weakly supervised pan-cancer segmentation tool

• Weakly Supervised Registration of Prostate MRI and Histopathology Images

• Weakly-Supervised Ultrasound Video Segmentation with Minimal Annotations

• Weakly-Supervised Universal Lesion Segmentation with Regional Level Set Loss

• Whole Heart Mesh Generation For Image-Based Computational Simulations By Learning Free-From Deformations

• Whole Slide Images are 2D Point Clouds: Context-Aware Survival Prediction using Patch-based Graph Convolutional Networks

• You Only Learn Once: Universal Anatomical Landmark Detection