Review on 2D and 3D MRI Image Segmentation Techniques

被引:21
|
作者
Shirly, S. [1 ]
Ramesh, K. [1 ]
机构
[1] Anna Univ Reg Campus, Dept Comp Applicat, Tirunelveli 627007, Tamil Nadu, India
来源
CURRENT MEDICAL IMAGING REVIEWS | 2019年 / 15卷 / 02期
关键词
Magnetic resonance imaging; image segmentation; image processing; 2-dimensional; 3-dimensional image segmentation; C-MEANS ALGORITHM; GAUSSIAN MIXTURE MODEL; AUTOMATIC SEGMENTATION; CLASSIFICATION; FCM;
D O I
10.2174/1573405613666171123160609
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Background: Magnetic Resonance Imaging is most widely used for early diagnosis of abnormalities in human organs. Due to the technical advancement in digital image processing, automatic computer aided medical image segmentation has been widely used in medical diagnostics. Discussion: Image segmentation is an image processing technique which is used for extracting image features, searching and mining the medical image records for better and accurate medical diagnostics. Commonly used segmentation techniques are threshold based image segmentation, clustering based image segmentation, edge based image segmentation, region based image segmentation, atlas based image segmentation, and artificial neural network based image segmentation. Conclusion: This survey aims at providing an insight about different 2-Dimensional and 3-Dimensional MRI image segmentation techniques and to facilitate better understanding to the people who are new in this field. This comparative study summarizes the benefits and limitations of various segmentation techniques.
引用
收藏
页码:150 / 160
页数:11
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