Deep Learning Applications for Brain Tumor Detection in Medical Imaging

Deep learning is employed in this research to identify and categorize brain tumors in medical photographs. MRI scan records are used to train Convolutional Neural Networks (CNNs), which achieve high tumor localization accuracy by differentiating between tumor and non-tumor images. The segmentation method is improved by sophisticated models notably U-Net, which offer accurate tumor boundary mapping. By helping radiologists with early detection and enhancing treatment results, this method has substantial applications in medical diagnostics. This method can lower the risk of progression by streamlining diagnostic procedures and providing prompt intervention in cases of brain tumors through integration into healthcare systems.