A Survey Paper on MRI Segmentation Algorithms to Identify Amyotrophic Lateral Sclerosis


A Survey Paper on MRI Segmentation Algorithms to Identify Amyotrophic Lateral Sclerosis

A Mary Priya, D Peter Augustine, V B Kirubanand

A Mary Priya, D Peter Augustine, V B Kirubanand "A Survey Paper on MRI Segmentation Algorithms to Identify Amyotrophic Lateral Sclerosis" Published in International Journal of Trend in Research and Development (IJTRD), ISSN: 2394-9333, Special Issue | EIT-17 , March 2017, URL: http://www.ijtrd.com/papers/IJTRD8163.pdf

Amyotrophic Lateral Sclerosis (ALS),which is also mentioned as Lou Gehrig’s disease,is a continuous degenerative neuromuscularconcern influencing both Upper Motor Neuronand Lower Motor Neurons and especiallydistressing people in their forties to seventies. Inspite of the fact that the pathology of ALS hasbeen obviously illustrated somewhere else, theexact reasons by which the sickness advancesand the proficient ways of diagnosis throughvarious tools such as MRI are still inadequatelycomprehended regions of the solution.In such scenario, there is a compellingneed for right and accurate diagnosis of ALS tocontrol the progressiveness of it. It is themotivation behind this survey article to talkabout the most pertinent proposed MRIprocessing algorithms in the literature availablefrom the past and present which haveencountered changing degrees of achievement.This is in no way a comprehensive survey of thecurrent literature available; nevertheless, itshould serve as an exhaustive analysis of themost significant points of MRI processing todiagnose ALS.

Amyotrophic Lateral Sclerosis (ALS), Magnetic Resonance imaging (MRI), Segmentation, Self-organizing mapping, Kmeans, Fuzzy C-means


Special Issue | EIT-17 , March 2017

2394-9333

IJTRD8163
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