Mathematics and Computer Science, Volume 1 by unknow

Author:unknow
Language: eng
Format: epub
ISBN: 9781119879671
Publisher: Wiley-Scrivener
Published: 2023-08-15T00:00:00+00:00

Note

*Corresponding author: [email protected]

15

Feature Extraction and Selection for Classification of Brain Tumors

Saswata Das

Department of Radiophysics and Electronics, University of Calcutta, Calcutta, India

Abstract

When malignant masses grow in an uncontrolled way, then it produces obscureness in the boundaries, shape and location. Sometimes it produces imprecise feature values. So selection of proper feature is very necessary to classify the brain tumors and diagonose it correctly. In this case, the tumor image is contrast enhanced and segmented. The segmented image is edged by using canny edge detection algorithm. From this segmented edged image, the proper feature is extracted. After that, the feature is selected using genetic algorithm and particle swarm optimization algorithm. Finally, classifiers like decision tree, support vector machine, K-nearest neighbor, etc., are used to classify the images. Experimental results show that this method reduces the feature redundancy to produce high efficiency in reasonably low time. The aim of our study is to check whether the tumor is benign or malignant.

Keywords: Brain tumor, feature extraction, feature selection, classification, SVM, KNN

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