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Titolo:
BICAV: A block-iterative parallel algorithm for sparse systems with pixel-related weighting
Autore:
Censor, Y; Gordon, D; Gordon, R;
Indirizzi:
Univ Haifa, Dept Math, IL-31905 Haifa, Israel Univ Haifa Haifa Israel IL-31905 aifa, Dept Math, IL-31905 Haifa, Israel Univ Haifa, Dept Comp Sci, IL-31905 Haifa, Israel Univ Haifa Haifa Israel IL-31905 , Dept Comp Sci, IL-31905 Haifa, Israel Technion Israel Inst Technol, Dept Aerosp Engn, IL-32000 Haifa, Israel Technion Israel Inst Technol Haifa Israel IL-32000 L-32000 Haifa, Israel
Titolo Testata:
IEEE TRANSACTIONS ON MEDICAL IMAGING
fascicolo: 10, volume: 20, anno: 2001,
pagine: 1050 - 1060
SICI:
0278-0062(200110)20:10<1050:BABPAF>2.0.ZU;2-F
Fonte:
ISI
Lingua:
ENG
Soggetto:
CONVEX FEASIBILITY PROBLEMS; LANDWEBER ITERATION; RECONSTRUCTION; PROJECTION; ACCELERATION;
Keywords:
block-iterative; component averaging; image reconstruction; parallel processing; pixel-related weighting; sparse systems;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Clinical Medicine
Engineering, Computing & Technology
Citazioni:
31
Recensione:
Indirizzi per estratti:
Indirizzo: Censor, Y Univ Haifa, Dept Math, IL-31905 Haifa, Israel Univ Haifa HaifaIsrael IL-31905 Math, IL-31905 Haifa, Israel
Citazione:
Y. Censor et al., "BICAV: A block-iterative parallel algorithm for sparse systems with pixel-related weighting", IEEE MED IM, 20(10), 2001, pp. 1050-1060

Abstract

Component averaging (CAV) was recently introduced by Censor, Gordon, and Gordon as a new iterative parallel technique suitable for large and sparse unstructured systems of linear equations. Based on earlier work of Byrne andCensor, it uses diagonal weighting matrices, with pixel-related weights determined by the sparsity of the system matrix. CAV is inherently parallel (similar to the very slowly converging Cimmino method) but its practical convergence on problems of image reconstruction from projections is similar tothat of the algebraic reconstruction technique (ART). Parallel techniques are becoming more important for practical image reconstruction since they are relevant not only for supercomputers but also for the increasingly prevalent multiprocessor workstations. This paper reports on experimental results with a block-iterative version of component averaging (BICAV). When BICAVis optimized for block size and relaxation parameters, its very first iterates are far superior to those of CAV, and more or less on a par with ART. Similar to CAV, BICAV is also inherently parallel. The fast convergence is demonstrated on problems of image reconstruction from projections, using the SNARK93 image reconstruction software package. Detailed plots of various measures of convergence, and reconstructed images are presented.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 27/01/20 alle ore 08:00:54