Published Paper Details:

The principal controller of a human being is their brain. A brain tumor develops when cells in the brain grow and split abnormally; brain cancer develops when brain tumors continue to grow. Computer vision plays a significant role in the field of human health, replacing human judgement, which provides reliable results. The common imaging techniques for magnetic resonance imaging (MRI) that are likely to be the most dependable and comfortable include CT scans, X-rays, and MRI scans. MRI finds even the smallest objects. The goal of our paper is to raise knowledge about the many methods for using brain MRI to find brain tumors. In order to remove the noises that can be seen in an MR image, we finished pre-processing utilizing the bilateral filter (BF) in this analysis. Following this for accurate tumor region recognition were binary thresholding and Convolutional Neural Networks (CNN) segmentation algorithms. Datasets for training, testing, and validation are used. We can determine whether a brain tumor is there or not depending on our device. The outcomes that are produced can be evaluated using a variety of performance-tested measures, including accuracy, sensitivity, and specificity. It is reported that the proposed development may demonstrate higher-quality functionality than its competitors.