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LMS-Net: A learned Mumford-Shah network for binary few-shot medical image segmentation.

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第一作者： Shengdong,Zhang

第一单位： Department of Mathematics, School of Science, Shanghai University, Shanghai, 200444, China.

作者： Shengdong,Zhang ^[1] ; Fan,Jia ^[2] ; Xiang,Li ^[3] ; Hao,Zhang ^[1] ; Jun,Shi ^[4] ; Liyan,Ma ^[5] ; Shihui,Ying ^[6]

作者单位： Department of Mathematics, School of Science, Shanghai University, Shanghai, 200444, China. ^[1] Department of Mathematics and Scientific Computing and Imaging (SCI) Institute, University of Utah, Salt Lake City, 84102, UT, USA. ^[2] School of Computer Science and Technology, East China Normal University, Shanghai, 200444, China. ^[3] School of Communication and Information Engineering, Shanghai University, Shanghai, 200444, China. ^[4] School of Computer Engineering and Science, Shanghai University, Shanghai, 200444, China; School of Mechatronic Engineering and Automation, Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, Shanghai University, Shanghai, 200444, China. Electronic address: liyanma@shu.edu.cn. ^[5] Shanghai Institute of Applied Mathematics and Mechanics, Shanghai, 200072, China; School of Mechanics and Engineering Science, Shanghai University, Shanghai, 200072, China. Electronic address: shying@shu.edu.cn. ^[6]

关键词 Deep denoising prior Deep unfolding network Few-shot semantic segmentation Mumford-Shah model

医学主题词人类(Humans);算法(Algorithms);图像处理, 计算机辅助(Image Processing, Computer-Assisted);图像解释, 计算机辅助(Image Interpretation, Computer-Assisted)

DOI 10.1016/j.media.2025.103676

PMID 40554256

发布时间 2025-08-24

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