Implementation of K-means segmentation algorithm on Intel Xeon Phi and GPU: Application in medical imaging

Abstract

The paper presents speed up of the k-means algorithm for image segmentation. This speed up is achieved by effective parallelization. For parallel implementation we focus on Many Integrated Core (MIC) architecture with Intel Xeon Phi coprocessors. The MIC implementation is compared with GPU, CPU and sequential implementation. To demonstrate parallel capabilities of k-means algorithm, segmentation of CT images of human body are used. Results of this work will be used for development of the software application for automatic 3D model reconstruction of heart and liver.