A Review of Multimodal Medical Image Fusion Techniques

被引:130
作者
Huang, Bing [1 ]
Yang, Feng [1 ,2 ]
Yin, Mengxiao [1 ,2 ]
Mo, Xiaoying [1 ]
Zhong, Cheng [1 ,2 ]
机构
[1] Guangxi Univ, Sch Comp & Elect & Informat, Nanning 530004, Guangxi, Peoples R China
[2] Guangxi Key Lab Multimedia Commun Network Technol, Nanning, Peoples R China
基金
中国国家自然科学基金;
关键词
NONSUBSAMPLED CONTOURLET TRANSFORM; COUPLED NEURAL-NETWORK; PET; WAVELET; MRI; FRAMEWORK; FILTER; IHS; CT;
D O I
10.1155/2020/8279342
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
The medical image fusion is the process of coalescing multiple images from multiple imaging modalities to obtain a fused image with a large amount of information for increasing the clinical applicability of medical images. In this paper, we attempt to give an overview of multimodal medical image fusion methods, putting emphasis on the most recent advances in the domain based on (1) the current fusion methods, including based on deep learning, (2) imaging modalities of medical image fusion, and (3) performance analysis of medical image fusion on mainly data set. Finally, the conclusion of this paper is that the current multimodal medical image fusion research results are more significant and the development trend is on the rise but with many challenges in the research field.
引用
收藏
页数:16
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