Home > Archive > 2011 > Volume 1 Number 4 (Oct. 2011) >
IJIET 2011 Vol.1(4): 280-285 ISSN: 2010-3689
DOI: 10.7763/IJIET.2011.V1.45

New methods in Brain MR Segmentation with Fuzzy EM algorithm

Soodabeh Safa and 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.

Index Terms—Brain MRI segmentation; fuzzy expected maximization; histogram based k-mean.

Authors are with Faculty of Computer Science and Information Technology University Putra Malaysia Selangor, Malaysia (e-mail: Soodabeh_safa@yahoo.com, bokharaeian@gmail.com).


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.

General Information

  • ISSN: 2010-3689 (Online)
  • Abbreviated Title: Int. J. Inf. Educ. Technol.
  • Frequency: Monthly
  • DOI: 10.18178/IJIET
  • Editor-in-Chief: Prof. Dr. Steve Thatcher
  • Executive Editor: Ms. Nancy Y. Liu
  • Abstracting/ Indexing: Scopus (CiteScore 2022: 2.0), INSPEC (IET), UGC-CARE List (India), CNKI, EBSCO, Google Scholar
  • E-mail: ijiet@ejournal.net


Article Metrics in Dimensions