Implementation of K-means segmentation algorithm on Intel Xeon Phi and GPU: Application in medical imaging. (January 2017)

• Record Type: Journal Article
• Authors: Jaroš, Milan; Strakoš, Petr; Karásek, Tomáš; Říha, Lubomír; Vašatová, Alena; Jarošová, Marta; Kozubek, Tomáš
• Is Part Of: Advances in engineering software. Volume 103(2017)
• Page Start: 21
• Page End: 28
• Publication Date: 2017-01
• Subjects: Image processing -- K-means -- Liver -- Computed tomography -- CT images -- GPU -- MIC -- Intel Xeon Phi -- Coprocessors; Computer-aided engineering -- Periodicals; Engineering -- Computer programs -- Periodicals; Engineering -- Software -- Periodicals; Periodicals; 620.0028553
• DOI: 10.1016/j.advengsoft.2016.05.008
• Languages: English
• ISSNs: 0965-9978

Abstract

Highlights: In our paper actual problems of medical image processing are being solved. We present acceleration of the image segmentation algorithm and show its further possible utilization for 3D model reconstructions of human body organs. Our attention has been drawn to utilization of modern and popular Intel Xeon Phi accelerators which offer many integrated cores for computational purposes. 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.