Brain Tumor Detection

Abstract

Human brain is the major controller of the humanoid
system. The abnormal growth and division of cells in the brain lead to a brain tumor, and further growth leads to brain cancer. In the area of human health, Computer Vision plays a significant role, which reduces the human judgment that gives accurate results. CT scans, X-Ray, and MRI scans are the common imaging methods among magnetic resonance imaging (MRI) that are the most reliable
and secure. MRI detects every minute object. Our paper aims to focus
on the discovery of brain cancer using brain MRI. In this study, we performed pre-processing using the Gaussian filter (BF) to remove the noises in an MRI image. This was followed by the binary thresholding and Convolution Neural Network (CNN) segmentation techniques for reliable detection of the tumor region. Training, testing, and validation datasets are used. Based on our machine, we
will predict whether the subject has a brain tumor or not. The resultant outcomes will be examined through various performance examined metrics that include accuracy, sensitivity, and specificity. It is desired that the proposed work would exhibit a more exceptional performance than its counterparts.