SPA: Efficient User-Preference Alignment against Uncertainty in Medical
Image Segmentation
SPA: Efficient User-Preference Alignment against Uncertainty in Medical
Image Segmentation
Medical image segmentation data inherently contain uncertainty, often stemming from both imperfect image quality and variability in labeling preferences on ambiguous pixels, which depend on annotators' expertise and the clinical context of the annotations. For instance, a boundary pixel might be labeled as tumor in diagnosis to avoid under-assessment of …