Context Independent Expectation Maximization Algorithm for Segmentation of Brain MR Images

Jasni, Mohamad Zain and Ahmed, M. Masroor and Rana, M.T.A (2012) Context Independent Expectation Maximization Algorithm for Segmentation of Brain MR Images. In: Proceedings of International Conference on Advanced Computer Science Applications and Technologies (ACSAT 2012), 26-28 November 2012 , Kuala Lumpur. pp. 436-441..

[img] PDF (fskkp-2012-jasni-Context Independent Expectation)
mahmood2.pdf - Published Version
Restricted to Repository staff only

Download (265kB) | Request a copy


For analyzing neurological disorders, realistic analysis of brain MRIs serves as a prerequisite step. This realistic analysis can be best described by segmenting the image into its constituent parts. Unfortunately, segmentation carried out by human visual system (HVS) is always influenced by certain factors. For example, inter-observer, intra-observer variability and large medical datasets. These factors make routine clinical applicability of HVS, a non practical way of examining MRIs. Therefore, to address this problem a fully automatic method is need of the hour. This paper discusses a highly efficient method i.e. the Expectation Maximization (EM) that precisely separates various parts of brain from a brain MRI. It works on the phenomenon of pixel labeling. The results obtained through this method are quite encouraging and are likely to contribute significantly in analyzing brain MRIs

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Users 134 not found.
Date Deposited: 04 Aug 2014 04:34
Last Modified: 21 May 2018 05:23
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item