The main supervisor of the anthropomorphic structure is the human brain. Brain tumors are caused by inappropriate brain development and division of cells, As and as brain tumors keep growing, brain cancer appears. Although it reduces the requirement for human judgment to obtain accurate findings, computer vision is significant in the field of human health. CT, X-ray, and MRI scans are the most dependable and secure common MRI (magnetic resonance imaging) procedures. MRI finds even the smallest items. This article focuses on the application of various methods for brain MRI-assisted brain cancer detection. In this research, we used the bilateral filter (BF) for pre-processing to eliminate noise since magnetic resonance images. For the purpose of accurately identifying the tumor location, probabilistic thresholding and Convolution Neural Network (CNN) methods for segmentation were then applied. Datasets for testing, validation, and training are used. We shall determine the possibility that the individual in question possesses a brain tumor according to our machine. Sensitivity, specificity, and accuracy are just a few of the measures of performance that may be used to evaluate the final results.