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An improved U-Net network for medical image segmentation

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成果类型:
期刊论文
作者:
Zhenzhen Wang;Jia Zhang;Zhihuan Liu;Shaomiao Chen;Danqing Lu
作者机构:
[Zhihuan Liu] College of Computer & Information Engineering, Central South University of Forestry and Technolog, Changsha, Hunan, China
[Zhenzhen Wang; Jia Zhang; Danqing Lu] College of Science, Central South University of Forestry and Technology, Changsha, Hunan, China
[Shaomiao Chen] School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan, Hunan, China
语种:
英文
期刊:
2023 IEEE 10th International Conference on Cyber Security and Cloud Computing (CSCloud)/2023 IEEE 9th International Conference on Edge Computing and Scalable Cloud (EdgeCom)
年:
2023
页码:
292-297
基金类别:
10.13039/501100014879-Central South University of Forestry and Technology
机构署名:
本校为第一机构
院系归属:
理学院
摘要:
In many computer-aided spinal imaging and disease diagnosis, automating the segmentation of the spine and cones from CT images is a challenging problem. Therefore, in this paper, we propose a triple channel expansion attention segmentation network based on U-Net for spinal CT images. We design a triple channel expansion attention to solve the problem of low accuracy caused by the loss of important feature information in the downsampling process of ordinary convolution, which uses different sizes of convolution set kernels to extract different features. Then through this attention, we output a ...

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