Detection Of MRI Brain Tumor Using Customized Deep Learning Method Via Web App

This article presents Multi-modal MRI scans used to classify brain tumors according to their size and imaging appearance. Object detection has been significantly improved by utilizing convolutional neural networks and deep learning approaches, resulting in superior performance. Our solution to tackle uncertainty involves a new deep learning method that incorporates pre-processing techniques such as data augmentation, as well as a customized convolutional neural network. The proposed method aims to achieve three objectives. (1) To address overfitting concerns, pre-processing techniques such as data augmentation are employed. (2) A customized deep learning method is used, which includes a convolutional neural network, to classify brain tumors. (3) A Web APP is utilized to provide information related to the tumor. The suggested procedure's performance is evaluated using sensitivity, specificity, and accuracy, and it outperforms traditional deep learning methods. Additionally, the entire process can be completed on the Python platform.