Author(s): C. Saranya Jothi, V. Usha, S. Alex David, Hijaj Mohammed

Email(s): saranyajothi22@gmail.com , husha88@gmail.com , alex_art2002@yahoo.co.uk , hijaj.mohammed@gmail.com

DOI: 10.5958/0974-360X.2018.00158.0   

Address: C. Saranya Jothi, V. Usha, S. Alex David, Hijaj Mohammed
Department of Computer Science and Engineering
Vel Tech Rangarajan Dr. Sagunthala R&D Institute of science and Technology, Avadi, Chennai-62
*Corresponding Author

Published In:   Volume - 11,      Issue - 3,     Year - 2018


ABSTRACT:
Automatic image classification is most important process in medical imaging for analyzing difference between normal patients and those who have the possibility of having abnormalities or tumor. MRI image consists of different gray levels and intensities. Brain tumor is varied in size and shape. Radiologist can diagnose and find location of lesions based on visual diagnosis with help of available software. While performing visual diagnosis, error may be introduced in finding location of tumor. To solve this problem there is need to develop a computer based automatic technique for detecting and classifying tumor from brain MRI images. The proposed system classifies the abnormalities in brain tumor by extracting the feature from brain tumor image and normal image using the GLCM and DWT. From the features classified by the classifier into two classes normal and abnormal along with different type of tumor by using the multiclass SVM which will give a promising result.


Cite this article:
C. Saranya Jothi, V. Usha, S. Alex David, Hijaj Mohammed. Abnormality Classification of Brain Tumor in MRI Images using Multiclass SVM. Research J. Pharm. and Tech. 2018; 11(3): 851-856. doi: 10.5958/0974-360X.2018.00158.0


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RNI: CHHENG00387/33/1/2008-TC                     
DOI: 10.5958/0974-360X 

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