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Keywords: adaptive mesh refinement, domain decomposition, elastic image registration, KAIRA, parallel algorithm, PermonFLLOP, TFETI.

Summary

Medical images are increasingly being used within healthcare for diagnosis, planning treatment and monitoring disease progression. The images acquired at different times, with different imaging modalities, from different subjects etc. often provide an additional clinical information that is not revealed in the separate images. Given two images, the goal of image registration is to find an optimal transformation in such way that one image becomes, in a certain sense, similar to the second one. In this paper, elastic image registration is used which assumes that the images are two different observations of an elastic body. The related elasticity problem is solved by using the Total FETI, which is a variant of the finite element tearing and interconnecting (FETI) domain decomposition method for massively parallel numerical solution of elliptic partial differential equations with optimal complexity. Because the medical images usually contain a small area of changes, a regular discretization results in a waste of computational resources (especially in three-dimensions). To avoid this, adaptive mesh refinement is used, with a coarser grid with local refinement in the region of interest. Parallelisation of the adaptive mesh refinement algorithm was done using the software tool KAIRA.

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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 18 Parallel Elastic Image Registration based on TFETI Method with Local Refinement S. Bohm¹, A. Ronovsky¹ and A. Vasatova^1,2 ¹IT4Innovations - Centre of Excellence Project, Ostrava, Czech Republic ²Department of Applied Mathematics, FEI, VSB - Technical University of Ostrava, Czech Republic doi:10.4203/ccp.107.18 purchase the full-text of this paper Full Bibliographic Reference for this paper S. Bohm, A. Ronovsky, A. Vasatova, "Parallel Elastic Image Registration based on TFETI Method with Local Refinement", in , (Editors), "Proceedings of the Fourth International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering", Civil-Comp Press, Stirlingshire, UK, Paper 18, 2015. doi:10.4203/ccp.107.18 Keywords: adaptive mesh refinement, domain decomposition, elastic image registration, KAIRA, parallel algorithm, PermonFLLOP, TFETI. Summary Medical images are increasingly being used within healthcare for diagnosis, planning treatment and monitoring disease progression. The images acquired at different times, with different imaging modalities, from different subjects etc. often provide an additional clinical information that is not revealed in the separate images. Given two images, the goal of image registration is to find an optimal transformation in such way that one image becomes, in a certain sense, similar to the second one. In this paper, elastic image registration is used which assumes that the images are two different observations of an elastic body. The related elasticity problem is solved by using the Total FETI, which is a variant of the finite element tearing and interconnecting (FETI) domain decomposition method for massively parallel numerical solution of elliptic partial differential equations with optimal complexity. Because the medical images usually contain a small area of changes, a regular discretization results in a waste of computational resources (especially in three-dimensions). To avoid this, adaptive mesh refinement is used, with a coarser grid with local refinement in the region of interest. Parallelisation of the adaptive mesh refinement algorithm was done using the software tool KAIRA. 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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