Detection and Classification of Brain Tumors

The incidence of brain tumors is increasing rapidly particularly in the young generation. Tumors can directly destroy all healthy brain cells. Manual (Physical) classification can cause human error. Automatic classification method is required because it reduces the load on the human observer, accura...

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Bibliographic Details
Published in:International journal of computer applications 2015-01, Vol.112 (8)
Main Authors: Chavan, Nikita V, Jadhav, B D, Patil, P M
Format: Article
Language:English
Subjects:
Brain
Classification
Classifiers
Feature extraction
Manuals
Surface layer
Texture
Tumors
Online Access:Get full text
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Summary:The incidence of brain tumors is increasing rapidly particularly in the young generation. Tumors can directly destroy all healthy brain cells. Manual (Physical) classification can cause human error. Automatic classification method is required because it reduces the load on the human observer, accuracy is not affected due to large number of images. This paper elaborates attempt to detection & classification of tumor in benign stage. The proposed method consists of two stages namely feature extraction and classification. In the first stage, obtained the features related to MRI images using Gray Level Co-occurrence Matrix (GLCM) based methods, this is one of the tools for extracting texture features and second stage, the classifier is classified images using K-nearest neighbour (K -NN) classifier.
ISSN:0975-8887
0975-8887
DOI:10.5120/19690-1439