Technology of Graphic & Image
|
1910-1915

Generating model constraints graph cuts label fusion algorithm

Zhang Lingshuna
Ma Yub
Lu Yuea
Wang Wennaa
Shen Wangfaa
a. School of Physics & Electronic-Electrical Engineering, b. Student Affairs Office, Ningxia University, Yinchuan 750021, China

Abstract

The segmentation algorithm of brain magnetic resonance image is easily affected by error label. In order to reduce the influence of the error label to label fusion method, and improve the brain MR image segmentation accuracy, this paper proposed an atlases selecting method based on the gradient information and mutual information in the pre-selection stage. And proposed the method of GM constraints graph cuts in the label fusion stage, to rapidly and accurately segment the hippocampus. Compared with the others label fusion method, the proposed method has higher segmentation accuracy.

Foundation Support

宁夏自然科学基金资助项目(NZ16009)
宁夏高等学校科学研究项目(NGY2016015)
2018年宁夏研究生教育教学改革研究与实践项目(YJG201811)
宁夏大学研究生创新研究项目(GIP2018071)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.12.0955
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 6
Section: Technology of Graphic & Image
Pages: 1910-1915
Serial Number: 1001-3695(2020)06-064-1910-06

Publish History

[2020-06-05] Printed Article

Cite This Article

张令顺, 马瑜, 芦玥, 等. 基于生成模型约束的graph cuts标签融合算法 [J]. 计算机应用研究, 2020, 37 (6): 1910-1915. (Zhang Lingshun, Ma Yu, Lu Yue, et al. Generating model constraints graph cuts label fusion algorithm [J]. Application Research of Computers, 2020, 37 (6): 1910-1915. )

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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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