Accurate Brain Tumor Detection using Deep Learning: A Comprehensive Review and Implementation Study

The objective of this study is to develop a detailed method for applying deep learning techniques to the early diagnosis of brain tumors. It is imperative that brain tumor is diagnosed as early as possible to ensure the best possible treatment. Due to its potential to enhance the precision and efficiency of cancer detection, deep learning techniques have become increasingly popular in areas related to medical image analysis. In the proposed system, Recurrent Neural Networks (RNNs) and Convolutional Neural Networks (CNNs) are used to analyze medical images, including CT and MRI scans. To raise the caliber of the input data, preprocessing methods like segmentation and picture enhancement are used. Brain scan abnormalities, lesions, and tumor regions can be automatically recognized by the trained deep-learning model.