Deep learning architectures for Brain Tumor detection: A Survey

Abstract

Deep learning methods are used in various fields of medical imaging like medical image localization/Detection segmentation, classification, and registration. Various medical conditions can be detected, monitored, and treated with deep learning techniques. One such condition is brain tumors. The main cause of brain tumors is the fast and uncontrolled development of brain cells. Over time, numerous techniques for detecting brain tumors have been developed. Manual analysis of brain tumor images will be time-consuming and it requires expert radiologists. Deep learning techniques can solve this issue since it is a fully automated process. Various deep learning architectures are used nowadays for different pattern recognition tasks in medical imaging. This survey aims to deliver different recent deep learning models developed to detect brain tumors and to present the drawbacks of existing techniques.