1Head, Department of Computer Science and Applications, The Gandhigram Rural Institute-Deemed University, Gandhigram, TamilNadu, India
2Research scholar, Department of Computer Science and Applications, GRI-DU, Gandhigram, TamilNadu, India
3M. Phil scholar, Department of Computer Science and Applications, GRI-DU, Gandhigram, TamilNadu, India
4Research scholar, Department of Computer Science and Applications, Gandhigram Rural Institute-Deemed University, Gandhigram, TamilNadu, India
Online published on 19 April, 2019.
Alzheimer Disease (AD) is one of the brain related disease that occur due to aging. It affects the brain, degenerate and kills the brain cells therefore causes the shrinkage in the brain tissues. The detection of AD in brain images is very cruicial in present times. In this paper, we proposed a method for detecting the Alzheimer disease in MRI human head scans by segmenting the WM and GM using Spatial Fuzzy Clustering Method (SFCM). This proposed method is a two-tier process, the Tier1 consists of brain portion extraction using skull stripping method and the segmentation of White Matter (WM) and Gray Matter (GM) using SFCM with level set method is processed in Tier2. The WM and GM are further analyzed to detect Alzheimer disease in MR brain images. Moreover, our method is evaluated by the similarity measures such as Jaccard (J) and Dice (D) to assess the efficiency.
Alzheimer Disease, Spatial Fuzzy Clustering with Level Set Method, Magnet Resonance Imaging
