Analysis of Brain Tumor Progression Methods Used in Deep Learning-Based Brain MRI Tumor Diagnosis

Brain tumors present a major challenge in medical research due to their high morbidity and mortality rates. Magnetic Resonance Imaging (MRI) remains the leading non-invasive technique for analyzing these tumors. In recent years, significant advancements in deep learning models and the increasing availability of extensive datasets have driven remarkable progress in brain tumor progression analysis using MRI data. This article explores state-of-the-art deep learning models applied to MRIbased brain tumor prognosis, examining experimental findings and the technical challenges. Additionally, it investigates prognosis-related datasets, efforts in regulatory frameworks, and inconsistencies in benchmarking standards.