Brain MR Image Segmentation and Bias Correction Model Based on Non-local Information

Due to the intensity inhomogeneous and noise in brain magnetic resonance(MR) image, it is difficult for the traditional models to obtain desirable segmentation results.In this paper, we first propose a novel model based on fuzzy C means(FCM) which combines segmentation with bias correction, while the non-local method is used as a regularization term to reduce the impact of noise as well as keep the image structure.Then, we introduce the artificial bee colony algorithm to gain the convex optimal solution.Experiments of the brain MR images show that the proposed method can obtain better segmentation results as well as the bias estimation in an accurate way.