doi: 10.7763/IJIET.2011.V1.45
New methods in Brain MR Segmentation with Fuzzy EM algorithm
Soodabeh Safa
,
Behrouz Bokharaeian
Abstract
Expectation maximization algorithm has been extensively used in a variety of medical image processing applications, especially for detecting human brain disease. In this paper, an efficient and improved semi-automated Fuzzy EM based techniques for 3-D MR segmentation of human brain images is presented. FEM along with histogram based Kmeans in initialization step is used for the labeling of individual pixels/voxels of a 3D anatomical MR image (MRI) into the main tissue classes in the brain, Gray matter (GM), White matter (WM), CSF (Celebro-spinal fluid). FEM‘s membership function were estimated through a histogram-based method. The results show our proposed FEM-KMeans has better performance and convergence speed compare to histogram based EM.
Keywords
- Brain MRI segmentation
- fuzzy expected maximization
- histogram based k-mean
How to Cite
Soodabeh Safa and Behrouz Bokharaeian, "New methods in Brain MR Segmentation with Fuzzy EM algorithm," International Journal of Information and Education Technology, vol. 1, no. 4, pp. 280-285, 2011. https://doi.org/10.7763/IJIET.2011.V1.45
Copyright & License
Copyright © 2011 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).