A parallel algorithm for 3D reconstruction of angiographic images

  • R. Rivas
  • M. B. Ibáñez
  • Y. Cardinale
  • P. Windyga
Track C1: (Industrial) End-user Applications of HPCN
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1593)


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.


Load Balance Reconstruction Process Work Unit Sequential Algorithm Superposition Condition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag 1999

Authors and Affiliations

  • R. Rivas
    • 1
  • M. B. Ibáñez
    • 2
  • Y. Cardinale
    • 2
  • P. Windyga
    • 3
  1. 1.Facultad de Ciencias. Escuela de ComputaciónUniversidad Central de VenezuelaCaracasVenezuela
  2. 2.Departamento de Computación y Tecnología de la InformaciónUniversidad Simón BolívarCaracasVenezuela
  3. 3.School of Computer ScienceUniversity of Central FloridaOrlando

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