PAPER ID: IJIM/Vol. 8 (IX) January 2024/8-16/2

AUTHOR: Mr. Rajendra Singh^[I],  Dr. Shiv Kant^[II]

TITLE: BRAIN TUMOR DETECTION USING BRAIN ACTIVITY THROUGH A CNN

ABSTRACT: A brain tumor is an abnormal growth of cells in the brain, with potential implications for cancer development. The primary method for detecting brain tumors is through Magnetic Resonance Imaging (MRI) scans, which provide crucial information about abnormal tissue growth. In numerous research papers, the utilization of machine learning and deep learning algorithms for brain tumor detection has gained prominence. These algorithms, when applied to MRI images, enhance the speed and accuracy of brain tumor prediction, facilitating prompt treatment for patients. Moreover, these predictions play a pivotal role in aiding radiologists in swift decision-making processes. This study introduces a novel approach employing a self-defined Artificial Neural Network (ANN) and Convolutional Neural Network (CNN) for the detection and performance evaluation of brain tumor analysis.

KEYWORDS: Brain Tumor Detection, Classification, Email Notification, CNN, Deep Learning

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