Segmentation Method of Stroke Lesions Based on Bidirectional Recurrent U-Net Model

Segmentation Method of Stroke Lesions Based on Bidirectional Recurrent U-Net Model

Stroke has a high disability rate and fatality rate. It is of great clinical significance to study the automatic recognition and segmentation of stroke lesions. Convolutional neural network can not make use of time sequence correlation of medical image data, and has the problem of low feature utiliz...

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Bibliographic Details
Main Authors: Xiaohui JIA, Xueying ZHANG, Suzhe WANG, Haisheng HUI, Fenglian LI, Hua ZHANG
Format: Article
Language:English
Published: Editorial Office of Journal of Taiyuan University of Technology 2022-11-01
Series:Taiyuan Ligong Daxue xuebao
Subjects:
deep learning
segmentation of stroke lesions
cgru
u-net
bidirectional feature fusion
multiplane fusion
Online Access:https://tyutjournal.tyut.edu.cn/englishpaper/show-1996.html

Internet

https://tyutjournal.tyut.edu.cn/englishpaper/show-1996.html

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