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Research Journal of Pharmacy and Technology
Year : 2020, Volume : 13, Issue : 6
First page : ( 2573) Last page : ( 2577)
Print ISSN : 0974-3618. Online ISSN : 0974-360X.
Article DOI : 10.5958/0974-360X.2020.00458.8

Brain Tumour Segmentation and Measurement Based on Threshold and Support Vector Machine Classifier

Ganesan P1,*, Sathish B. S.2, Elamaran V.3, Murugesan R.4

1Department of Electronics and Communication Engineering, Vidya Jyothi Institute of Technology, Hyderabad, India

2Department of Electronics and Communication Engineering, Ramachandra College of Engineering, Eluru, India

3Department of Electronics and Communication Engineering, School of EEE, SASTRA Deemed University, Thanjavur, India

4Department of Electronics and Communication Engineering, Narsimha Reddy Engineering College, Secunderabad, Telangana, India

*Corresponding Author E-mail: gganeshnathan@gmail.com, subramanyamsathish@yahoo.co.in

Online published on 4 July, 2020.


In medical image processing, the detection and segmentation of brain tumor from the test image is the challenging but most important task. According to WHO, the brain tumor is second most common of cancer death among young people. The proposed approach for the brain tumor segmentation is worked on the principle of threshold and classification using support vector machine. The brain image of the brain is processed in such a way so that the tumor is extracted and displayed the segmented the tumor portion of the image. The gray level co-occurrence matrix and other image quality measures are utilized to calculate the statistical features of the extracted tumor portion of brain. Based on the extracted features, the category of tumor, either benign or malignant, is classified using SVM classifier.



Brain tumor, Principal Component Analysis, Threshold, GLCM.


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