TEXTURE ANALYSIS OF BRAIN TUMOR IN DIGITIZED MRI USING GLEASON AND MENHINICK DIVERSITY INDEX

Authors

  • SHRADHA .S.CHAVAN Department of Electronics and Telecom Engineering, JSPMs, Jayawantrao Sawaat College of Engineering, Savitribai Phule Pune University, Pune, India
  • PRATIMA P. GUMASTE Research Scholar, Dept. of Electronics and Telecom, JSPMs, Rajarshi Shahu College of Engineering, Savitribai Phule Pune University, Pune, India

Keywords:

Brain tumor, MRI image,, segmentation, MATLAB.

Abstract

Tumor is swelling of the body part, due to this abnormal growth of cells in that place of the body. If it is in brain called brain tumor. Brain tumor is diagnosed by the magnetic resonance imaging (MRI). In the propose methodology, we firstly detect and extract tumor using watershed segmentation. To increase the efficiency of texture feature extraction, the diversity index’s capability to detect patterns of tumor. The Gleason and Menhinick indexes are used. At the end, the extracted texture of brain tumor image is classified using the Support Vector Machine, looking to differentiate the malignant and benign class of tumor.

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Published

2021-02-22

Issue

Vol. 3 No. 09 (2017): Journalnx

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to Cite

TEXTURE ANALYSIS OF BRAIN TUMOR IN DIGITIZED MRI USING GLEASON AND MENHINICK DIVERSITY INDEX. (2021). JournalNX - A Multidisciplinary Peer Reviewed Journal, 3(09), 56-60. https://repo.journalnx.com/index.php/nx/article/view/2292