Quantitative Assessment of Chest CT Patterns in COVID-19 and Bacterial Pneumonia Patients: a Deep Learning Perspective.
Dual attention multiple instance learning with unsupervised complementary loss for COVID-19 screening.
Weakly supervised segmentation on neural compressed histopathology with self-equivariant regularization.
Content preserving image translation with texture co-occurrence and spatial self-similarity for texture debiasing and domain adaptation.
One-shot Federated Learning on Medical Data using Knowledge Distillation with Image Synthesis and Client Model Adaptation.
Attention guided multi-scale cluster refinement with extended field of view for amodal nuclei segmentation.
