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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 8, ISSUE 11, NOVEMBER 2019

Development of Improved Classification and Segmentation Technique for Brain Tumor Detection

Ashima Gupta, Navneet Agrawal

DOI: 10.17148/IJARCCE.2019.81127

Abstract: The tumor can be detected by segmentation of brain Magnetic Resonance Image (MRI). In the case of suspected brain tumor, the exact location and size of tumor can be determined by radiologist. In this work tumor is detected by various stages like pre-processing, segmentation, feature extraction and classifier. The approach of otsu segmentation is applied for the segmentation. Tumor feature is extracted by Discrete Wavelet Transform (DWT) and Gray Level Co-occurrence Matrix (GLCM). Classification is done by using hidden markov model and performance parameters are measured.

Keywords: HMM, Otsu’s segmentation, GLCM

How to Cite:

[1] Ashima Gupta, Navneet Agrawal, “Development of Improved Classification and Segmentation Technique for Brain Tumor Detection,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2019.81127