From Pixels to Decisions: A Comprehensive Review of Brain Tumor Classification Techniques and Their Clinical Implications

With the increasing prevalence of medical imaging, the need for efficient and accurate image analysis techniques has grown significantly. Artificial Intelligence has evolved as an effective tool to support medical image analysis, especially in the detection and classification of various diseases, including brain tumors. This paper presents an overview of latest improvements in deep learning-based brain tumor detection and classification. The state-of-art techniques of brain tumor classification have been discussed with details of base technology, benchmark datasets and evaluation metrics for providing insights into the performance of different approaches. The integration of deep learning in medical image analysis holds great promise in enhancing diagnostic accuracy and expediting treatment planning for improved treatment routine.