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SAMCT: Segment Any CT Allowing Labor-Free Task-Indicator Prompts
March 21, 2024, 4:45 a.m. | Xian Lin, Yangyang Xiang, Zhehao Wang, Kwang-Ting Cheng, Zengqiang Yan, Li Yu
cs.CV updates on arXiv.org arxiv.org
Abstract: Segment anything model (SAM), a foundation model with superior versatility and generalization across diverse segmentation tasks, has attracted widespread attention in medical imaging. However, it has been proved that SAM would encounter severe performance degradation due to the lack of medical knowledge in training and local feature encoding. Though several SAM-based models have been proposed for tuning SAM in medical imaging, they still suffer from insufficient feature extraction and highly rely on high-quality prompts. In …
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