Survey of brain tumor segmentation with deep neural networks

Abstract

A brain tumour is a serious condition that, if not diagnosed and treated early on, can lead to death. Researchers have proposed a variety of traditional and recently developed deep learning based segmentation and classification approaches for determining the condition of the tumor. Deep learning is found to be efficient and robust for classification and segmentation as it detects the fine-to-coarse information about the tumors. The main component of deep learning is layered neural network architecture popularly known as convolutional neural network. Distinct information from brain images can be acquired and analysed depending on the architecture. In order to achieve high segmentation and classification accuracy, more research is required in this area. In this paper presents a review of state-of-the-art deep learning methods for brain tumor segmentation and deep learning neural networks, clearly highlighting their building blocks and different strategies. Finally, this article implying about present status on segmentation and classification of tumor-based image processing through deep learning models.