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Open Access Research

Spatial based Expectation Maximizing (EM)

M A Balafar

Author affiliations

Dept of IT, Faculty of Electric and Computer, University of Tabriz, Tabriz, East Azerbaijan, Iran

Citation and License

Diagnostic Pathology 2011, 6:103  doi:10.1186/1746-1596-6-103

Published: 26 October 2011

Abstract

Background

Expectation maximizing (EM) is one of the common approaches for image segmentation.

Methods

an improvement of the EM algorithm is proposed and its effectiveness for MRI brain image segmentation is investigated. In order to improve EM performance, the proposed algorithms incorporates neighbourhood information into the clustering process. At first, average image is obtained as neighbourhood information and then it is incorporated in clustering process. Also, as an option, user-interaction is used to improve segmentation results. Simulated and real MR volumes are used to compare the efficiency of the proposed improvement with the existing neighbourhood based extension for EM and FCM.

Results

the findings show that the proposed algorithm produces higher similarity index.

Conclusions

experiments demonstrate the effectiveness of the proposed algorithm in compare to other existing algorithms on various noise levels.

Keywords:
Em; Segmentation; Neighbourhood