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International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering
International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2321-2004ISSN Print 2321-5526Since 2013
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← Back to VOLUME 10, ISSUE 7, JULY 2022

BRAIN TUMOR DETECTION USING DEEP LEARNING

Archana Y S,, Prof. B P Soumya

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Abstract: The development of aberrant brain cells, some of which may turn cancerous, is known as a brain tumor. Magnetic Resonance Imaging (MRI) scans are the most common technique for finding brain tumors. Information about the aberrant tissue growth in the brain is discernible from the MRI scans. In numerous research papers, machine learning and deep learning algorithms are used to detect brain tumors. It takes extremely little time to forecast a brain tumor when these algorithms are applied to MRI pictures, and the better accuracy makes it easier to treat patients. The radiologist can make speedy decisions thanks to these predictions. A self-defined KNN and Naive Bayes is used in the proposed study to identify brain tumors and related

Keywords: KNN, NaΓ―ve Bayes, MRI Scan, Images.

How to Cite:

[1] Archana Y S,, Prof. B P Soumya, β€œBRAIN TUMOR DETECTION USING DEEP LEARNING,” International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering (IJIREEICE), DOI: 10.17148/IJIREEICE.2022.10729

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