Progress of the segmentation methods of magnetic resonance image and its application
10.3760/cma.j.issn.1673-4181.2013.03.009
- VernacularTitle:核磁共振图像分割算法及应用进展
- Author:
Qing LUO
;
Wenjian QIN
;
Jia GU
;
Ying JI
- Publication Type:Journal Article
- Keywords:
Magnetic resonance image segmentation;
Threshold;
Pattern recognition;
Active contours;
Markov random field;
Graph cut
- From:
International Journal of Biomedical Engineering
2013;36(3):165-171
- CountryChina
- Language:Chinese
-
Abstract:
Magnetic resonance imaging (MRI) plays a more and more important role in medical image area for its advantages of nonradiative,multiple imaging and high spatial resolution.This review gives a systematic discussion over a couple of MRI segmentation algorithms that are used widely to help people have an entire knowledge of MRI segmentation methods.On the base of classification and summary of MRI segmentation,the MRI segmentation algorithms have been classified into 5 different categories after preliminary investigation and survey.Based on threshold,pattern recognition,active contours,Markov random field (MRF) and graph cut,separately.After further investigation and survey we summarize the characters and field of applications of the 5 different algorithms,then take a few segment experiments among these algorithms on abdomen MRI and present their distinct characteristics.At last,we take a prospect at the future of the MRI segmentation.
