A Robust Information Fuzzy Clustering Algorithm for Medical Image Segmentation

Abstract

In order to improve the robustness of the conventional fuzzy C-means (FCM) clustering algorithms for image segmentation, a robust information fuzzy clustering algorithm is proposed in this paper. This is an extension of the information-theoretic framework into the FCM-type algorithms. Combining these two concepts and modifying the objective function of the FCM algorithm, we are able to solve the sensitivity of noisy data and the lack of spatial information problems and improve the image segmentation results. The experimental results have shown that this robust clustering algorithm is useful for the MRI brain image segmentation and yield better segmentation results when compared to the conventional FCM approach.