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@article{152900,
        author = {Bhavani S and Shilpa Nayak R L and Sirasappa Y Pattar},
        title = {DETECTION AND CLASSIFICATION OF BRAIN TUMOR},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {5},
        pages = {19-24},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=152900},
        abstract = {Brain and other nervous system cancer is the tenth leading reason of death for men and women. Brain tumors account for 85% to 90% of all number one nervous system (CNS) tumors. Detection of a brain tumor is always important specifically whilst affected person’s survival depends upon correct time evaluation due to massive and diverse quantity of statistics manual detection of brain tumor may be very tedious and tough challenge. Moreover, computerized brain detection is always hard trouble due to the fact the structure of mind and distinct variations in MRIs. Image segmentation has usually been the essential task for the automatic detection of the brain tumor. This assignment proposes a technique wherein mind pix are preprocessed and segmented and additionally we employ CNN architecture algorithms to detect the type of tumor.},
        keywords = {Brain Tumor, Machine Learning, Neural Networks, Segmentation},
        month = {},
        }