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Paper 7

Parallelization of the Image Segmentation Algorithm for Intel Xeon Phi with Application in Medical Imaging

P. Strakos¹, M. Jaros¹, T. Karasek¹, L. Riha¹, M. Jarosova¹, T. Kozubek¹, P. Vavra² and T. Jonszta²

¹IT4I, VSB - Technical University of Ostrava, Czech Republic
²Faculty of Medicine, University of Ostrava, Czech Republic

doi:10.4203/ccp.107.7

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P. Strakos, M. Jaros, T. Karasek, L. Riha, M. Jarosova, T. Kozubek, P. Vavra, T. Jonszta, "Parallelization of the Image Segmentation Algorithm for Intel Xeon Phi with Application in Medical Imaging", in , (Editors), "Proceedings of the Fourth International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering", Civil-Comp Press, Stirlingshire, UK, Paper 7, 2015. doi:10.4203/ccp.107.7

Keywords: image processing, k-means, liver, computed tomography, abdominal images, MIC, Intel Xeon Phi, coprocessors.

Summary

In this paper speed up of the k-means algorithm for image segmentation is presented. This speed up is achieved by effective parallelization. For parallel implementation the MIC architecture Intel Xeon Phi coprocessor has been selected. To demonstrate parallel capabilities of k-means algorithm segmentation of CT images the abdominal part of the body is used. The results of this work will be used for development of the software application for the automatic three-dimensional model reconstruction of the heart and liver.

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Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Proceedings ISSN 1759-3433 CCP: 107 PROCEEDINGS OF THE FOURTH INTERNATIONAL CONFERENCE ON PARALLEL, DISTRIBUTED, GRID AND CLOUD COMPUTING FOR ENGINEERING Edited by: Paper 7 Parallelization of the Image Segmentation Algorithm for Intel Xeon Phi with Application in Medical Imaging P. Strakos¹, M. Jaros¹, T. Karasek¹, L. Riha¹, M. Jarosova¹, T. Kozubek¹, P. Vavra² and T. Jonszta² ¹IT4I, VSB - Technical University of Ostrava, Czech Republic ²Faculty of Medicine, University of Ostrava, Czech Republic doi:10.4203/ccp.107.7 purchase the full-text of this paper Full Bibliographic Reference for this paper P. Strakos, M. Jaros, T. Karasek, L. Riha, M. Jarosova, T. Kozubek, P. Vavra, T. Jonszta, "Parallelization of the Image Segmentation Algorithm for Intel Xeon Phi with Application in Medical Imaging", in , (Editors), "Proceedings of the Fourth International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering", Civil-Comp Press, Stirlingshire, UK, Paper 7, 2015. doi:10.4203/ccp.107.7 Keywords: image processing, k-means, liver, computed tomography, abdominal images, MIC, Intel Xeon Phi, coprocessors. Summary In this paper speed up of the k-means algorithm for image segmentation is presented. This speed up is achieved by effective parallelization. For parallel implementation the MIC architecture Intel Xeon Phi coprocessor has been selected. To demonstrate parallel capabilities of k-means algorithm segmentation of CT images the abdominal part of the body is used. The results of this work will be used for development of the software application for the automatic three-dimensional model reconstruction of the heart and liver. purchase the full-text of this paper (price £20) go to the previous paper go to the next paper return to the table of contents return to the book description purchase this book (price £45 +P&P)
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