Brain tumor detection using deep learning and convolutional neural network from magnetic resonance images

Abstract

Brain tumor detection is a critical medical procedure aimed at identifying newlineabnormal regions within the brain. Traditionally, this has been achieved through newlineinvasive methods, involving the insertion of foreign materials into the brain to newlinelocate tumors. Unfortunately, this approach is not only time-consuming but also newlineinflicts significant pain on patients, often resulting in blood loss. To address these newlinedrawbacks and improve patient comfort, an alternative non-invasive method has newlinebeen proposed for the detection and localization of brain tumor regions. This novel newlineapproach relies on scanning techniques, specifically Computer Tomography (CT) newlineand Magnetic Resonance Imaging (MRI). In this thesis, the focus is on employing newlinethe MRI scanning technique for tumor region detection and segmentation. newlineBy exploring the potential of non-invasive methods like MRI, we aim to revolutionize newlinebrain tumor detection, making it more patient-friendly, efficient, and accurate. newlineThrough this research, we hope to contribute to the advancement of medical imaging newlinetechnology, ultimately enhancing healthcare outcomes for patients with brain tumors. newline newline