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