4 papers
CoDiR: Confidence-Guided Diffusion Refinement for Semi-Supervised Histopathology Segmentation
Hoai Nhan Pham, Dang-Nguyen Bui, Le-Van Thai +7
Semi-supervised histopathology segmentation is challenging due to scarce annotations and unreliable pseudo-labels in ambiguous gland regions. To address this problem, we propose Co…
ProBAG: Prototype-Guided Boundary-Aware Graph Diffusion for Weakly Supervised Histopathology Segmentation
Duy-Dong Nguyen, Le-Van Thai, Hoai Nhan Pham +3
Weakly supervised semantic segmentation enables histopathology tissue segmentation from image-level annotations, avoiding costly pixel-level labeling by expert pathologists. Howeve…
UniSemAlign: Text-Prototype Alignment with a Foundation Encoder for Semi-Supervised Histopathology Segmentation
Le-Van Thai, Tien Dat Nguyen, Hoai Nhan Pham +3
Semi-supervised semantic segmentation in computational pathology remains challenging due to scarce pixel-level annotations and unreliable pseudo-label supervision. We propose UniSe…
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…