A parallel algorithm for 3D reconstruction of angiographic images
Accurate diagnosis and therapeutic evaluation of coronary dysfunction is possible by tri-dimensional (3D) visualization of Coronary arteries. Reconstruction based on bi-dimensional (2D) images can be presented as a discrete optimization problem. A blind search cannot be applied, instead a Branch-and-Bound algorithm is used to explore the state space and give an intermediate result. The heuristic information used is based on knowledge based filtering in coronagraphy.
A sequential algorithm using suitable filters leads to implementations where the execution time is measured in days. In order to minimize the execution time we propose to apply parallel computing techniques.
The critical issue in parallel search algorithms is the distribution of the search space among the processors. We propose a technique to compute the total amount of work units among the processors. The technique is based on the enlargement of segments (unitary threads) representing pieces of arteries. We achieve a good load balancing and the speedup obtained is nearly optimum.
KeywordsLoad Balance Reconstruction Process Work Unit Sequential Algorithm Superposition Condition
Unable to display preview. Download preview PDF.
- 1.I. Foster. Designing and building parallel programs. Concepts and tools for Parallel Software Engineering. Addison Wesley, 1995.Google Scholar
- 2.W. Group, E. Lusk, and A. Skjellum. Using M.P.I. The MIT Press, 1994.Google Scholar
- 3.R. W. Hockney. The Science of Computer Benchmarking. SIAM, 1996.Google Scholar
- 4.Lydia Kronsjo and Dean Shumsheruddin. Advances in parallel algorithms. John Wiley and sons, 1992.Google Scholar
- 5.V Kumar, A Grama, A Gupta, and G Karypis. Introduction to parallel computing. Design and analysis of algorithms. The Benjamin/Cummings, 1994.Google Scholar
- 6.A. La Cruz, G. Morinelli, P. Windyga, G. Bevilacqua, and J. Silva. ANIA: A tool for angiographic image analysis and study. In XVII IEEE-EMBC Conference, pages 381–382, Montreal, Canada, 1995. IEEE.Google Scholar
- 7.G. Passariello and F. Mora. Imagenología Médica. Equinoccio, 1995.Google Scholar
- 8.P. Windyga. Evaluation et modelisation de connaissances pour la reconstruction tridimensional du reseau vasculaire cardiaque en angiographie biplan. PhD Thesis, Univ. Rennes France, 1994.Google Scholar
- 9.P. Windyga, G. Bevilacqua, J. L. Coatrieux, and M. Garreau. Estimation of searchspace in 3D coronary artery reconstruction using angiographic biplane images. In XVII IEEE-EMBC Conference, pages 389–390, Montreal, Canada, 1995. IEEE.Google Scholar
- 10.P. Windyga, I. López, G. Bevilacqua, M. Garreau, and J. L. Coatrieux. Utility of 2D properties in the reconstruction of coronary arteries from biplane angiographic images. In XVII IEEE-EMBC Conference.Google Scholar
- 11.P. Windyga, Garreau M., Shah M., Coatrieux J. L., and LeBreton H. Three-dimensional reconstruction of the coronary arteries using a priori knowledge. In Medical and Biological Engineering and Computing, pages 158–164. 36, 1998.Google Scholar