Deep learning for brain tumor segmentation

Abstract

Brain tumors are considered to be one of the most lethal types of tumor. Accurate segmentation of brain MRI is an important task for the analysis of neurological diseases. The mortality rate of brain tumors is increasing according to World Health Organization. Detection at early stages of brain tumors can increase the expectation of the patients’ survival. Concerning artificial intelligence approaches for clinical diagnosis of brain tumors, there is an increasing interest in segmentation approaches based on deep learning because of its ability of self-learning over large amounts of data. Deep learning is nowadays a very promising approach to develop effective solution for clinical diagnosis. This chapter provides at first some basic concepts and techniques behind brain tumor segmentation. Then the imaging techniques used for brain tumor visualization are described. Later on, the dataset and segmentation methods are discussed.