A survey of deep learning methods for MRI brain tumor image segmentation

Abstract

Automatic segmentation of MRI brain tumors based on deep learning can automatically extract more expressive and discriminative brain image features. In view of the application value of deep learning in brain tumor segmentation, this paper systematically reviews the deep learning methods for MRI brain tumor segmentation. Firstly, the research status and significance of brain tumor segmentation methods based on deep learning are analyzed in detail. The deep learning segmentation algorithm performs well, but there are also problems such as the poor ability to capture long-distance dependence and less labeled brain image data. This paper summarizes the principles and advantages of these algorithms and performs some algorithms. Finally, the future of MRI brain tumor segmentation methods is based on deep learning prospects.