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- Title
MULTIPLE SCLEROSIS LESIONS SEGMENTATION OF MR IMAGE USING PARTICLE REGION GROWING ALGORITHM.
- Authors
PANDIAN A.; UDHAYAKUMAR G.
- 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.
- Subjects
MULTIPLE sclerosis; BRAIN imaging; MAGNETIC resonance imaging; WHITE matter (Nerve tissue); GRAY matter (Nerve tissue)
- Publication
I-Manager's Journal on Image Processing, 2019, Vol 6, Issue 4, p11
- ISSN
2349-4530
- Publication type
Article
- DOI
10.26634/jip.6.4.16722