Glioma Segmentation-Oriented Multi-Modal MR Image Fusion With Adversarial Learning

被引：1

作者：

Yu Liu ^{[1
,2
,3
]}

Yu Shi ^{[2
,3
]}

Fuhao Mu ^{[2
,3
]}

Juan Cheng ^{[2
,3
]}

Xun Chen ^{[1
,4
,5
]}

机构：

[1] IEEE

[2] the Department of Biomedical Engineering, Hefei University of Technology

[3] the Anhui Province Key Laboratory of Measuring Theory and Precision Instrument, Hefei University of Technology

[4] the Department of Neurosurgery, the First Affiliated Hospital of USTC, Division of Life Sciences and Medicine

[5] the Department of Electronic Engineering and Information Science, University of Science and Technology of China

来源：

IEEE/CAA Journal of Automatica Sinica | 2022年 / 9卷 / 08期

关键词：

D O I：

暂无

中图分类号：

TP391.41 []; R739.41 [颅内肿瘤及脑肿瘤];

学科分类号：

080203 ; 100214 ;

摘要：

<正>Dear Editor,In recent years, multi-modal medical image fusion has received widespread attention in the image processing community. However,existing works on medical image fusion methods are mostly devoted to pursuing high performance on visual perception and objective fusion metrics, while ignoring the specific purpose in clinical applications.

引用

页码：1528 / 1531

页数：4

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