Title: A fast medical image segmentation method of based on initial contour forecast segmentation model

Authors: Yanjun Peng; Yuxiang Zhu; Yuanhong Wang

Addresses: Key Laboratory for Wisdom Mine Information Technology of Shandong Province, Shandong University of Science and Technology, Qingdao, 266590, China; College of Information Science and Engineering, Shandong University of Science and Technology, Qingdao, 266590, China ' College of Information Science and Engineering, Shandong University of Science and Technology, Qingdao, 266590, China ' College of Information Science and Engineering, Shandong University of Science and Technology, Qingdao, 266590, China

Abstract: A fast segmentation algorithm of single medical image and sequence images based on active contour model are proposed in this paper. We give out the initial contour forecast segmentation model of 3D medical image first, and then, numerical solution of the image segmentation model algorithm is presented, send data blocks to different processors to do numerical calculations, finally combine the segmentation results. At the same time, parallel designing methods of node allocation, task allocation and load balancing methods are researched. The experiment results show that the parallel method can significantly improve the segmentation speed of 3D medical image.

Keywords: clustering; parallel design; image segmentation; active contour models; medical images; initial contour forecast segmentation; node allocation; task allocation; load balancing.

DOI: 10.1504/IJCSM.2016.077863

International Journal of Computing Science and Mathematics, 2016 Vol.7 No.3, pp.212 - 220

Received: 04 Apr 2016
Accepted: 13 Apr 2016
Published online: 17 Jul 2016 *

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