Medical SAM adapter: Adapting segment anything model for medical image segmentation

The Segment Anything Model (SAM) has recently gained popularity in the field of image segmentation due to its impressive capabilities in various segmentation tasks and its prompt-based interface. However, recent studies and individual experiments have shown that SAM underperforms in medical image se...

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Bibliographic Details

Published in:	Medical image analysis Vol. 102; p. 103547
Main Authors:	Wu, Junde, Wang, Ziyue, Hong, Mingxuan, Ji, Wei, Fu, Huazhu, Xu, Yanwu, Xu, Min, Jin, Yueming
Format:	Journal Article
Language:	English
Published:	Netherlands Elsevier B.V 01.05.2025
Subjects:	Algorithms Efficient Learning Fine-Tuning Humans Image Interpretation, Computer-Assisted - methods Image Processing, Computer-Assisted - methods Imaging, Three-Dimensional - methods Medical Image Segmentation Efficient Learning Fine-Tuning Medical Image Segmentation 41A10 65D05 65D17 41A05
ISSN:	1361-8415, 1361-8423, 1361-8423
Online Access:	Get full text
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