<ul><li>Accurate segmentation of polyps and skin lesions is crucial for diagnosing colorectal and skin cancers.</li><li>The pixel-level annotation of medical images is time-consuming and costly.</li><li>The paper proposes BiSeg-SAM, a weakly supervised post-processing framework for the segmentation of polyps and skin lesions.</li><li>BiSeg-SAM demonstrates superior performance compared to state-of-the-art methods in polyp and skin cancer segmentation.</li></ul>

BiSeg-SAM: Weakly-Supervised Post-Processing Framework for Boosting Binary Segmentation in Segment Anything Models

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