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Paper Title :
A Study of Feature Extraction and Selection Techniques for Brain Abnormalitites Classification

Author :Rupal Snehkunj, Ashish Jani

Article Citation :Rupal Snehkunj ,Ashish Jani , (2017 ) " A Study of Feature Extraction and Selection Techniques for Brain Abnormalitites Classification " , International Journal of Advances in Science, Engineering and Technology(IJASEAT) , pp. 44-46, Volume-5,Issue-1, Spl. Iss-2

Abstract : In this paper, we present a comparative study of various techniques which have been proposed for feature extraction and selection of brain abnormalities in MRI data. The techniques include GLCM, PCA, and LDA which are reviewed in this paper. In GLCM, it calculates the co-occurrence matrix of an image which are used to distinguish between normal and abnormal patient whereas PCA(principal component analysis) and LDA(linear discriminant analysis) are used to reduce the number of features which are retrieved after applying GLCM Simulation is done in MATLAB 2013a and results for the techniques are discussed.. Keywords- GLCM, PCA,LDA, brain abnormalities

Type : Research paper

Published : Volume-5,Issue-1, Spl. Iss-2


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