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Titolo: MEANVARIANCE ANALYSIS OF BLOCKITERATIVE RECONSTRUCTION ALGORITHMS MODELING 3D DETECTOR RESPONSE IN SPECT
Autore: LALUSH DS; TSUI BMW;
 Indirizzi:
 UNIV N CAROLINA,DEPT BIOMED ENGN CHAPEL HILL NC 27514 UNIV N CAROLINA,DEPT RADIOL CHAPEL HILL NC 00000
 Titolo Testata:
 IEEE transactions on nuclear science
fascicolo: 3,
volume: 45,
anno: 1998,
parte:, 2
pagine: 1280  1287
 SICI:
 00189499(1998)45:3<1280:MAOBRA>2.0.ZU;2L
 Fonte:
 ISI
 Lingua:
 ENG
 Soggetto:
 IMAGERECONSTRUCTION; TOMOGRAPHY; EMISSION;
 Tipo documento:
 Article
 Natura:
 Periodico
 Settore Disciplinare:
 Science Citation Index Expanded
 Science Citation Index Expanded
 Citazioni:
 10
 Recensione:
 Indirizzi per estratti:



 Citazione:
 D.S. Lalush e B.M.W. Tsui, "MEANVARIANCE ANALYSIS OF BLOCKITERATIVE RECONSTRUCTION ALGORITHMS MODELING 3D DETECTOR RESPONSE IN SPECT", IEEE transactions on nuclear science, 45(3), 1998, pp. 12801287
Abstract
We study the statistical convergence properties of two Cast iterativereconstruction algorithms, the rescaled blockiterative (RBI) and ordered subset (OS) EM algorithms, in the context of cardiac SPECT with 3D detector response modeling. The Monte Carlo method was used to generate nearly noisefree projection data modeling the effects of attenuation, detector response, and scatter from the MCAT phantom. One thousand noise realizations were generated with an average count level approximating a typical Tl201 cardiac study. Each noise realization was reconstructed using the RBI and OS algorithms for cases with and without detector response modeling. For each iteration up to twenty, we generated mean and variance images, as well as covariance images for six specific locations. Both OS and RBI converged in the mean to results thatwere close to the noisefree MLEM result using the same projection model. When detector response was not modeled in the reconstruction, RBI exhibited considerably lower noise variance than OS for the same resolution. When 3D detector response was modeled, the RBIEM provided a small improvement in the tradeoff between noise level and resolution recovery, primarily in the axial direction, while OS required about half the number of iterations of RBI to reach the same resolution. We conclude that OS is faster than RBI, but may be sensitive to errors in the projection model. Both OSEM and RBIEM are effective alternatives to the MLEM algorithm, but noise level and speed of convergence dependon the projection model used.
ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 20/01/20 alle ore 16:08:38