Domain Adaptation and Representation Transfer
A Systematic Benchmarking Analysis of Transfer Learning for Medical Image Analysis
Self-supervised Multi-scale Consistency for Weakly Supervised Segmentation Learning
FDA: Feature Decomposition and Aggregation for Robust Airway Segmentation
Adversarial Continual Learning for Multi-Domain Hippocampal Segmentation
Self-Supervised Multimodal Generalized Zero Shot Learning For Gleason Grading
Self-Supervised Learning of Inter-Label Geometric Relationships For Gleason Grade Segmentation
Stop Throwing Away Discriminators! Re-using Adversaries for Test-Time Training
Transductive image segmentation: Self-training and effect of uncertainty estimation
Unsupervised Domain Adaptation with Semantic Consistency across Heterogeneous Modalities for MRI Prostate Lesion Segmentation
Cohort Bias Adaptation in Federated Datasets for Lesion Segmentation
Exploring Deep Registration Latent Spaces
Learning from Partially Overlapping Labels: Image Segmentation under Annotation Shift
Unsupervised Domain Adaption via Similarity-based Prototypes for Cross-Modality Segmentation
Affordable AI and Healthcare
Classification and Generation of Microscopy Images with Plasmodium Falciparum via Arti cial Neural Networks using Low Cost Settings
Contrast and Resolution Improvement of POCUS Using Self-Consistent CycleGAN
Low-Dose Dynamic CT Perfusion Denoising without Training Data
Recurrent Brain Graph Mapper for Predicting Time-Dependent Brain Graph Evaluation Trajectory
COVID-Net US: A Tailored, Highly Efficient, Self-Attention Deep Convolutional Neural Network Design for Detection of COVID-19Patient Cases from Point-of-care Ultrasound Imaging
Inter-Domain Alignment for Predicting High-Resolution Brain Networks Using Teacher-Student Learning
Sickle Cell Disease Severity Prediction from Percoll Gradient Images using Graph Convolutional Networks
Continual Domain Incremental Learning for Chest X-ray Classification in Low-Resource Clinical Settings
Deep learning based Automatic detection of adequately positioned mammograms
Can non-specialists provide high quality Gold standard labels in challenging modalities.