ISSN : 2319-7323

INTERNATIONAL JOURNAL OF COMPUTER SCIENCE ENGINEERING

ABSTRACT

Title	:	IMPROVED CELLULAR AUTOMATA SEGMENTATION OF BRAIN TUMORS ON MR IMAGES AND SVM CLASSIFICATION
Authors	:	Sakthivel.S, Dr.P.Rajendran, Varun.M.R
Keywords	:	Brain tumor segmentation, cellular automata, contrast enhanced magnetic resonance imaging (MRI), necrotic tissue segmentation, seeded segmentation.
Issue Date	:	May 2014
Abstract	:	Image Processing is one of the developing research areas today. Medical image processing is the most demanding and hugely wanted field in image processing. Brain tumor recognition in Magnetic resonance imaging (MR) has grow to be an developing area in the field of medical image processing. In our paper Magnetic resonance imaging (MRI) is an imaging technique that has played an essential role in neuro science research for studying brain images. Classification is an main part in order to differentiate between normal patients and those who have the possibility of having abnormality or tumor. The proposed method consists of two stages: feature extraction and classification. In first stage features be extracted from images using ICA. In the next stage, extracted features are feed as input to SVM classifier. It classify the images between normal and abnormal along with type of disease depending upon features. . The aim of this paper is to design an automated tool for brain tumor detection using MRI scanned image records. Detection and extraction of tumor from MRI scan images of the brain was done using MATLAB software.
Page(s)	:	168-172
ISSN	:	2319-7323
Source	:	Vol. 3, No.3