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Multiple Sclerosis Lesions Segmentation of MR Image using Particle Region Growing Algorithm

Pandian A.*, Udhayakumar G.**

* Department of Electronics and Communication Engineering, SRM Valliammai Engineering College, Chennai, Tamil Nadu, India.

** Department of Electrical and Electronics Engineering, SRM Valliammai Engineering College, Chennai, Tamil Nadu, India.

Periodicity:October - December'2019
DOI : https://doi.org/10.26634/jip.6.4.16722

Abstract

The detection of Multiple Sclerosis (MS) brain tissue is essential for several neuroimaging studies. In this paper, we implement a Particle Region Growing Algorithm (PRGA) in order to segment brain tissue affected by the MS. To concentrate the brain, White Matter (WM) lesions are required more attention to find out the abnormal brain tissue along with normal brain tissue in T2W MRI brain image scan. However, the sensitivity and specificity of MS lesion detection and segmentation with the different method approaches have been inadequate. In this paper, we concentrate on the White Matter (WM) and Gray Matter (GM) of MS lesion affected the T2 weighted transverse view of the brain MR image. We carried out extensive experiments with MS patients MRI image data. In this work, we found a new approach that leads to a substantial improvement in the sensitivity and specificity of MS lesion detection by using a PRGA segmentation algorithm.

Keywords

Multiple Sclerosis Lesions (MS), Magnetic Resonance Image (MRI), Particle Region Growing Algorithm (PRGA).

How to Cite this Article?

Pandian, A., and Udhayakumar, G. (2019). Multiple Sclerosis Lesions Segmentation of MR Image using Particle Region Growing Algorithm. i-manager's Journal on Image Processing, 6(4), 11-17. https://doi.org/10.26634/jip.6.4.16722

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Multiple Sclerosis Lesions Segmentation of MR Image using Particle Region Growing Algorithm

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