Enhancements in Brain Tumor Detection and Classification Using Deep Learning on MRI Data
Sivakumar Depuru, M. Sunil Kumar
Abstract
Medical specialists must identify brain tumors rapidly and correctly because it enables proper treatment protocols. Magnetic Resonance Imaging (MRI) stands as the principal diagnostic tool for brain tumors because it provides outstanding soft-tissue differentiation and safe examination without requiring piercing the skin. The evaluation of MRI scans through manual methods becomes both a thorough process and a human fallible procedure which might trigger additional delays for diagnosis and therapy commencement. A review discusses modern developments regarding the application of machine learning methods for brain tumor detection and diagnosis through computers. The text emphasizes how convolutional neural networks together with multimodal data fusion approaches boost both handling efficiency and diagnostic precision. The article provides a complete investigation of brain tumor detection by addressing all stages from data collection and processing through modeling to evaluation and clinical validation as well as fundamental challenges and research paths for the future.