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Can SAM Segment Polyps?
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Recently, Meta AI Research releases a general Segment Anything Model (SAM), which has demonstrated promising performance in several segmentation tasks. As we know, polyp segmentation is a fundamental task in the medical imaging field, which plays a critical role in the diagnosis and cure of colorectal cancer. In particular, applying SAM to the polyp segmentation task is interesting. In this report, we evaluate the performance of SAM in segmenting polyps, in which SAM is under unprompted settings. We hope this report will provide insights to advance this polyp segmentation field and promote more interesting works in the future. This project is publicly at https://github.com/taozh2017/SAMPolyp.
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Cited by 1 Pith paper
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Mamba Guided Boundary Prior Matters: A New Perspective for Generalized Polyp Segmentation
SAM-MaGuP, a SAM-based polyp segmentation model with a 1D-2D Mamba adapter and boundary distillation, reports state-of-the-art mDice/mIoU on five public colonoscopy datasets.
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