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

被引：0

作者：

Xing, Wenyu ^{[1
,2
]}

Zhu, Zhibin ^{[3
]}

Hou, Dongni ^{[4
,5
]}

Yue, Yaoting ^{[1
,2
]}

Dai, Fei ^{[1
]}

Li, Yifang ^{[6
]}

Tong, Lin ^{[4
,5
]}

Song, Yuanlin ^{[4
,5
]}

Ta, Dean ^{[1
,7
]}

机构：

[1] Center for Biomedical Engineering, School of Information Science and Technology, Fudan University, Shanghai,200438, China

[2] Human Phenome Institute, Fudan University, Shanghai,200438, China

[3] School of Physics and Electromechanical Engineering, Hexi University, Zhangye,734000, China

[4] Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai,200032, China

[5] Shanghai Key Laboratory of Lung Inflammation and Injury, Shanghai,200032, China

[6] Academy for Engineering and Technology, Fudan University, Shanghai,200433, China

[7] Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai,200040, China

来源：

Computers in Biology and Medicine | 2022年 / 147卷

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D O I：

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摘要：

Automatic segmentations - Clinical diagnosis - Clinical evaluation - CM-segnet - Low contrast - Manual segmentation - Medical image segmentation - Multi scale analysis - Multilayers perceptrons - Segmentation models

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