Thresholded and Morphological Operations Based Brain Image Segmentation
S.Naganandhini1, P.Shanmugavadivu2
1S. Naganandhini, Research Scholar, Department of Computer Science and Applications The Gandhigram Rural Institute Deemed University Gandhigram, Dindigul, Tamil Nadu, India.
2P. Shanmugavadivu, Professor, Department of Computer Science and Applications, The Gandhigram Rural Institute Deemed University, Gandhigram, Dindigul, Tamil Nadu, India.
Manuscript received on 05 April 2019 | Revised Manuscript received on 14 April 2019 | Manuscript Published on 24 May 2019 | PP: 96-100 | Volume-8 Issue-6S3 April 2019 | Retrieval Number: F10170486S319/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Skull Stripping is an inevitable computer-assisted medical brain mage pre-processing mechanism thataims to segregate the non-designated regions, in order to extract the designated brain regions. Those resultant brain region images arefurther subjected to diagnostic analysis to discover the brain diseases/ disorders. This paper presents an efficient method named, Threshold and Morphological Operations based Segmentation, (TMOS) for skull stripping is, exclusively designed for MRI brain images (Magnetic Resonance Images). It has two phases: the first phase localizes the brain region using Region of Interest (RoI) and in the second phase, morphological operations are applied to precisely extract the brain region by stripping out the skull. The performance of TMOS is validated using Minimal Interval Resonance Image in Alzheimer Disease (MIRIAD) dataset. The accuracy of TMOS is visually confirmed.
Keywords: Skull Stripping, T1-Weighted MRI brain images, Otsu’s threshold, Region of Interest method, Morphological Operation.
Scope of the Article: Computer Science and Its Applications