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Segment Any Medical Model Extended
March 28, 2024, 4:45 a.m. | Yihao Liu, Jiaming Zhang, Andres Diaz-Pinto, Haowei Li, Alejandro Martin-Gomez, Amir Kheradmand, Mehran Armand
cs.CV updates on arXiv.org arxiv.org
Abstract: The Segment Anything Model (SAM) has drawn significant attention from researchers who work on medical image segmentation because of its generalizability. However, researchers have found that SAM may have limited performance on medical images compared to state-of-the-art non-foundation models. Regardless, the community sees potential in extending, fine-tuning, modifying, and evaluating SAM for analysis of medical imaging. An increasing number of works have been published focusing on the mentioned four directions, where variants of SAM are …
abstract art arxiv attention community cs.cv fine-tuning found foundation however image images medical performance researchers sam segment segment anything segment anything model segmentation state type work
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