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General Information
    • ISSN: 2010-3689
    • Frequency: Bimonthly (2011-2014); Monthly (Since 2015)
    • DOI: 10.18178/IJIET
    • Editor-in-Chief: Prof. Dr. Steve Thatcher
    • Executive Editor: Ms. Nancy Y. Liu
    • Abstracting/ Indexing: EI (INSPEC, IET), Electronic Journals Library, Google Scholar, Crossref and ProQuest
    • E-mail: ijiet@ejournal.net
Editor-in-chief
Prof. Dr. Steve Thatcher
University of South Australia, Australia
It is my honor to be the editor-in-chief of IJIET. The journal publishes good papers which focous on the advanced researches in the field of information and education technology. Hopefully, IJIET will become a recognized journal among the scholars in the filed of information and education technology.
IJIET 2012 Vol.2(4): 335-337 ISSN: 2010-3689
DOI: 10.7763/IJIET.2012.V2.145

Efficient Way of Skull Stripping in MRI to Detect Brain Tumor by Applying Morphological Operations, after Detection of False Background

Sajjad Mohsin, Sadaf Sajjad, Zeeshan Malik, and Abdul Hanan Abdullah

Abstract—Brain MRI is used to get deeper view of the brain conditions. Skull stripping is a major phase sometimes refers to a pre-process in MRI brain imaging applications which refers to the removal of brain non-cerebral tissues. Various algorithms have been developed to improve the effectiveness of stripping skull from MRI. Morphological algorithms of “Erosion” and “Dilation” are recursively applied together to remove the skull. Besides the removal of skull, “erosion” distorts some cerebral tissues due to the presence of false-background. So “Dilation” process is applied for the restoration. In this study, we improved the efficiency of stripping skull in MRI using systematic application of “Erosion” with AOI (Area of Interest) approach after the detection of false-background. Before applying “Erosion”, a false back ground is detected. We identified the skull boundary through Dilation and then used scan line algorithm to fill the false background area. Consequently “Erosion” algorithm will only erode the AOI, resulting in the stripping of skull without any effect on the other tissues of the brain. Results show that the accuracy rate up to 95% is obtained and 43% efficiency is increased as compared to the different morphological techniques used previously.

Index Terms—Skull stripping, AOI (area of interest), erosion, false background, dilation, morphology, MRI

S. Mohsin, S. Sajjad and Z. Malik are with COMSATS Institute of Information Technology, Pakistan (e-mail: smohsin@comsats.edu.pk).
S. Sajjad and A. H. Abdullah are with University Technology Malaysia, Malaysia.

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Cite: Sajjad Mohsin, Sadaf Sajjad, Zeeshan Malik, and Abdul Hanan Abdullah, "Efficient Way of Skull Stripping in MRI to Detect Brain Tumor by Applying Morphological Operations, after Detection of False Background," International Journal of Information and Education Technology vol. 2, no. 4, pp. 335-337, 2012.

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