Unsupervised Segmentation for Automatic Detection of Brain Tumors in MRI

In this paper, we present a new automatic segmentation method for magnetic resonance images. The aim of this segmentation is to divide the brain into homogeneous regions and to detect the presence of tumors. Our method is divided into two parts. First, we make a pre-segmentation to extract the brain from the head. Then, a second segmentation is done inside the brain. Several techniques are combined like anisotropic filtering or stochastic model-based segmentation during the two processes. The paper describes the main features of the method, and gives some segmentation results. Key-Words: MRI, Segmentation, anisotropic filtering, Markov Random Field, MAP criterion.