Lesion Segmentation from Imperfect Medical Data via Weakly Supervised Learning with SAM and Explainable Vision Transformer.
Accurate lesion segmentation remains a critical yet challenging task in medical imaging due to scarce pixel-level annotations, inter-observer variability and modality-specific noise. Conventional fully supervised models require exhaustive manual labeling, which limits scalability and clinical applicability. To address...