• M AnanthaLakshmi

In this paper segmentation of brain tumors from magnetic resonance imaging (MRI) datasets is of great importance for improved diagnosis, growth rate prediction and treatment planning. Brain tumor is one of the most dangerous disease. Therefore, brain tumor detection should be fast and accurate. The automatic brain tumor tissue detection allows to localize the mass of tumor cells in the Magnetic Resonance Images (MRI).MRI provides greater contrast between different soft tissues of human body. Hence, MRI is much more effective in brain and cancer imaging. The convolution neural network (CNN) having the proper sets of training data are able to distinguish between abnormal and normal tumor regions and classify them correctly as a tumor, malign tumor or healthy brain.

BRAIN IMAGE SEGMENTATION BASED ON GLCM ALGORITHM BY USING DIGITAL IMAGE PROCESSING

"BRAIN IMAGE SEGMENTATION BASED ON GLCM ALGORITHM BY USING DIGITAL IMAGE PROCESSING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 2, page no.b702-b712, February-2024, Available :http://www.jetir.org/papers/JETIR2402179.pdf

"BRAIN IMAGE SEGMENTATION BASED ON GLCM ALGORITHM BY USING DIGITAL IMAGE PROCESSING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 2, page no. ppb702-b712, February-2024, Available at : http://www.jetir.org/papers/JETIR2402179.pdf