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CM-SegNet: A deep learning-based automatic segmentation approach for medical images by combining convolution and multilayer perceptron.

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第一作者： Wenyu,Xing

第一单位： Center for Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai, 200438, China; Human Phenome Institute, Fudan University, Shanghai, 200438, China.

作者： Wenyu,Xing ^[1] ; Zhibin,Zhu ^[2] ; Dongni,Hou ^[3] ; Yaoting,Yue ^[1] ; Fei,Dai ^[4] ; Yifang,Li ^[5] ; Lin,Tong ^[6] ; Yuanlin,Song ^[6] ; Dean,Ta ^[7]

作者单位： Center for Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai, 200438, China; Human Phenome Institute, Fudan University, Shanghai, 200438, China. ^[1] School of Physics and Electromechanical Engineering, Hexi University, Zhangye, 734000, China. ^[2] Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China; Shanghai Key Laboratory of Lung Inflammation and Injury, Shanghai, 200032, China. Electronic address: hou.dongni@zs-hospital.sh.cn. ^[3] Center for Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai, 200438, China. ^[4] Academy for Engineering and Technology, Fudan University, Shanghai, 200433, China. ^[5] Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China; Shanghai Key Laboratory of Lung Inflammation and Injury, Shanghai, 200032, China. ^[6] Center for Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai, 200438, China; Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, 200040, China. Electronic address: tda@fudan.edu.cn. ^[7]

关键词 CM-SegNet Convolution Medical image segmentation Multilayer perceptron Multiscale analysis

医学主题词图像处理, 计算机辅助(Image Processing, Computer-Assisted);成像, 三维(Imaging, Three-Dimensional)

DOI 10.1016/j.compbiomed.2022.105797

PMID 35780603

发布时间 2022-09-16

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