Research progress of multi-model medical image fusion and recognition.
- Author:
Tao ZHOU
1
;
Huiling LU
1
;
Zhiqiang CHEN
2
;
Jingxian MA
1
Author Information
1. School of Science, Ningxia Medical University, Yinchuan 750004, China.
2. Department of Radiology, the Affiliated General Hospital of Ningria Medical University, Yinchuan 750004, China.
- Publication Type:Journal Article
- MeSH:
Algorithms;
Artificial Intelligence;
Diagnostic Imaging;
methods;
Image Enhancement;
methods;
Image Interpretation, Computer-Assisted;
methods;
Image Processing, Computer-Assisted;
methods;
Magnetic Resonance Imaging;
methods;
Pattern Recognition, Automated;
methods;
Positron-Emission Tomography;
methods;
Tomography, X-Ray Computed;
methods
- From:
Journal of Biomedical Engineering
2013;30(5):1117-1122
- CountryChina
- Language:Chinese
-
Abstract:
Medical image fusion and recognition has a wide range of applications, such as focal location, cancer staging and treatment effect assessment. Multi-model medical image fusion and recognition are analyzed and summarized in this paper. Firstly, the question of multi-model medical image fusion and recognition is discussed, and its advantage and key steps are discussed. Secondly, three fusion strategies are reviewed from the point of algorithm, and four fusion recognition structures are discussed. Thirdly, difficulties, challenges and possible future research direction are discussed.
