Machine Learning
Advances in Machine Learning Theory
Towards Robust General Medical Image Segmentation
Joint Motion Correction and Super Resolution for Cardiac Segmentation via Latent Optimisation
Targeted Gradient Descent: A Novel Method for Convolutional Neural Networks Fine-tuning and Online-learning
A Hierarchical Feature Constraint to CamouflageMedical Adversarial Attacks
Group Shift Pointwise Convolution for Volumetric Medical Image Segmentation
Machine Learning
Attention models
UTNet: A Hybrid Transformer Architecture for Medical Image Segmentation
AlignTransformer: Hierarchical Alignment of Visual Regions and Disease Tags for Medical Report Generation
Continuous-Time Deep Glioma Growth Models
Spine-Transformers: Vertebra Detection and Localization in Arbitrary Field-of-View Spine CT with Transformers
Multi-view analysis of unregistered medical images using cross-view transformers
Machine Learning
Domain Adaptation
Stain Mix-up: Unsupervised Domain Generalization for Histopathology Images
A Unified Hyper-GAN Model for Unpaired Multi-contrast MR Image Translation
Generative Self-training for Cross-domain Unsupervised Tagged-to-Cine MRI Synthesis
Cooperative Training and Latent Space Data Augmentation for Robust Medical Image Segmentation
Controllable cardiac synthesis via disentangled anatomy arithmetic
CoTr: Efficiently Bridging CNN and Transformer for 3D Medical Image Segmentation
Harmonization with Flow-based Causal Inference
Uncertainty-Aware Label Rectification for Domain Adaptive Mitochondria Segmentation
Semantic Consistent Unsupervised Domain Adaptation for Cross-modality Medical Image Segmentation
Anatomy of Domain Shift Impact on U-Net Layers in MRI Segmentation
FoldIt: Haustral Folds Detection and Segmentation in Colonoscopy Videos
Reference-Relation Guided Autoencoder with Deep CCA Restriction for Awake-to-Sleep Brain Functional Connectome Prediction
Domain Composition and Attention for Unseen-Domain Generalizable Medical Image Segmentation
Fully Test-time Adaptation for Image Segmentation
OLVA: Optimal Latent Vector Alignment for Unsupervised Domain Adaptation in Medical Image Segmentation
Prototypical Interaction Graph for Unsupervised Domain Adaptation in Surgical Instrument Segmentation
Unsupervised Domain Adaptation for Small Bowel Segmentation using Disentangled Representation
Data-driven mapping between functional connectomes using optimal transport
EndoUDA: A modality independent segmentation approach for endoscopy imaging
Style Transfer Using Generative Adversarial Networks for Multi-Site MRI Harmonization
Machine Learning
Federated Learning
Federated Semi-supervised Medical Image Classification via Inter-client Relation Matching
FedPerl: Semi-Supervised Peer Learning for Skin Lesion Classification
Personalized Retrogress-Resilient Framework for Real-World Medical Federated Learning
Federated Whole Prostate Segmentation in MRI with Personalized Neural Architectures
Federated Contrastive Learning for Volumetric Medical Image Segmentation
Federated Contrastive Learning for Decentralized Unlabeled Medical Images
Machine Learning
Interpretability / Explainability
Explaining COVID-19 and Thoracic Pathology Model Predictions by Identifying Informative Input Features
Demystifying T1-MRI to FDG18-PET Image Translation via Representational Similarity
Fairness in Cardiac MR Image Analysis: An Investigation of Bias Due to Data Imbalance in Deep Learning Based Segmentation
An Interpretable Approach to Automated Severity Scoring in Pelvic Trauma
Scalable, Axiomatic Explanations of Deep Alzheimer's Diagnosis from Heterogeneous Data
SPARTA: An Integrated Stability, Discriminability, and Sparsity based Radiomic Feature Selection Approach
The Power of Proxy Data and Proxy Networks for Hyper-Parameter Optimization for Medical Image Segmentation
Fighting Class Imbalance with Contrastive Learning
Interpretable gender classification from retinal fundus images using BagNets
Explainable Classification of Weakly Annotated Wireless Capsule Endoscopy Images based on a Fuzzy Bag-of-Colour Features Model and Brain Storm Optimization
Towards Semantic Interpretation of Thoracic Disease and COVID-19 Diagnosis Models
A Principled Approach to Failure Analysis and Model Repairment: Demonstration in Medical Imaging
Using Causal Analysis for Conceptual Deep Learning Explanation
A spherical convolutional neural network for white matter structure imaging via diffusion MRI
Sharpening Local Interpretable Model-agnostic Explanations for Histopathology: Improved Understandability and Reliability
Improving the Explainability of Skin Cancer Diagnosis Using CBIR
PAC Bayesian Performance Guarantees for (Stochastic) Deep Networks in Medical Imaging
Machine Learning
Uncertainty
Medical Matting: A New Perspective on Medical Segmentation with Uncertainty
Confidence-aware Cascaded Network for Fetal Brain Segmentation on MR Images
Orthogonal Ensemble Networks for Biomedical Image Segmentation
Learning to Predict Error for MRI Reconstruction
Uncertainty-Guided Progressive GANs for Medical Image Translation
Variational Topic Inference for Chest X-Ray Report Generation
Uncertainty Aware Deep Reinforcement Learning for Anatomical Landmark Detection in Medical Images.