• Pallak
• Brahmaleen Kaur Sidhu

Unnecessary growth of the tissue is very communal problem in current health care scenario. Segmentation of the image is commonly used to extract the uncharacteristic tumour percentage in human’s brain. Brain tumor is a very serious problem which is the growth of heavy mass of tissue in the brain and increase nonstop, speciously controlling of irregular cells mechanism. Various approaches have been discussed for tumor detections in the brain. Our central point is on the approaches which deal with the image segmentation and classification to sense human brain tumor. So this paper deals with the review of the various scenarios and processes which were used by the researchers for the automatic classification of the tumor from brain topographies which is a significant part but also the time consuming process which is generally performed in the medical field by the medical experts.

Classifications, Segmentation's, Supervise and unsupervised learning

"AN EFFECTUAL CALSSIFICATION OF AUTOMATIC BRAIN TUMORS: A REVIEW", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 12, page no.400-404, December-2018, Available :http://www.jetir.org/papers/JETIR1812866.pdf

"AN EFFECTUAL CALSSIFICATION OF AUTOMATIC BRAIN TUMORS: A REVIEW", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 12, page no. pp400-404, December-2018, Available at : http://www.jetir.org/papers/JETIR1812866.pdf