5 papers
Handling Supervision Scarcity in Chest X-ray Classification: Long-Tailed and Zero-Shot Learning
Ha-Hieu Pham, Hai-Dang Nguyen, Thanh-Huy Nguyen +4
Chest X-Ray (CXR) classification in clinical practice is often limited by imperfect supervision, arising from (i) extreme long-tailed multi-label disease distributions and (ii) mis…
ConStruct: Structural Distillation of Foundation Models for Prototype-Based Weakly Supervised Histopathology Segmentation
Khang Le, Ha Thach, Anh M. Vu +9
Weakly supervised semantic segmentation (WSSS) in histopathology relies heavily on classification backbones, yet these models often localize only the most discriminative regions an…
DualProtoSeg: Simple and Efficient Design with Text- and Image-Guided Prototype Learning for Weakly Supervised Histopathology Image Segmentation
Anh M. Vu, Khang P. Le, Trang T. K. Vo +13
Weakly supervised semantic segmentation (WSSS) in histopathology seeks to reduce annotation cost by learning from image-level labels, yet it remains limited by inter-class homogene…
LPD: Learnable Prototypes with Diversity Regularization for Weakly Supervised Histopathology Segmentation
Khang Le, Anh Mai Vu, Thi Kim Trang Vo +7
Weakly supervised semantic segmentation (WSSS) in histopathology reduces pixel-level labeling by learning from image-level labels, but it is hindered by inter-class homogeneity, in…
Contrastive Integrated Gradients: A Feature Attribution-Based Method for Explaining Whole Slide Image Classification
Anh Mai Vu, Tuan L. Vo, Ngoc Lam Quang Bui +7
Interpretability is essential in Whole Slide Image (WSI) analysis for computational pathology, where understanding model predictions helps build trust in AI-assisted diagnostics. W…