Recent Advances in Sparse Representation Based Medical Image Fusion

被引：28
|
作者：
Liu, Yu [1 ]
Chen, Xun [2 ,3 ]
Liu, Aiping [4 ]
Ward, Rabab K. [5 ,6 ,7 ,8 ]
Wang, Z. Jane [5 ,9 ]
机构：
[1] Hefei Univ Technol, Dept Biomed Engn, Hefei, Peoples R China
[2] USTC, Affiliated Hosp 1, Dept Neurosurg, Div Life Sci & Med, Hefei, Peoples R China
[3] Univ Sci & Technol China, Dept Elect Engn & Informat Sci, Hefei, Peoples R China
[4] Univ Sci & Technol China, Dept Elect Sci & Technol, Hefei, Peoples R China
[5] Univ British Columbia, Dept Elect & Comp Engn, Vancouver, BC, Canada
[6] Royal Soc Canada, Ottawa, ON, Canada
[7] Canadian Acad Engineers, Natl Acad Engn, Ottawa, ON, Canada
[8] Engn Inst Canada, Ottawa, ON, Canada
[9] Canadian Acad Engineers, Ottawa, ON, Canada
来源：
IEEE INSTRUMENTATION & MEASUREMENT MAGAZINE | 2021年 / 24卷 / 02期
基金：
中国国家自然科学基金;
关键词：
Three-dimensional displays; Image representation; Market research; Distance measurement; Medical diagnostic imaging; Image fusion; Biomedical measurement; Biomedical monitoring; Medical diagnosis; MRI DATA FUSION; K-SVD; DICTIONARIES; ALGORITHM;
D O I：
10.1109/MIM.2021.9400960
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Medical image fusion, which aims to combine multi-source information captured by different imaging modalities, is of great significance to medical professionals for precise diagnosis and treatment. In the last decade, sparse representation (SR)-based approach has emerged as a very active direction in the field of medical image fusion, due to its powerful ability for image representation. In this paper, we mainly present an overview of the recent advances achieved in SR-based medical image fusion, ranging from the conventional local and single-component SR-based methods to the latest global and multi-component SR-based methods. In addition, several major challenges remained in this direction are presented and some future prospects are discussed.
引用
收藏
页码：45 / 53
页数：9
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