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Titolo: Fast maximum entropy approximation in SPECT using the RBIMAP algorithm
Autore: Lalush, DS; Frey, EC; Tsui, BMW;
 Indirizzi:
 Univ N Carolina, Dept Biomed Engn, Chapel Hill, NC 27599 USA Univ N Carolina Chapel Hill NC USA 27599 Engn, Chapel Hill, NC 27599 USA Univ N Carolina, Dept Radiol, Chapel Hill, NC 27599 USA Univ N Carolina Chapel Hill NC USA 27599 adiol, Chapel Hill, NC 27599 USA
 Titolo Testata:
 IEEE TRANSACTIONS ON MEDICAL IMAGING
fascicolo: 4,
volume: 19,
anno: 2000,
pagine: 286  294
 SICI:
 02780062(200004)19:4<286:FMEAIS>2.0.ZU;2F
 Fonte:
 ISI
 Lingua:
 ENG
 Soggetto:
 ITERATIVE RECONSTRUCTION ALGORITHMS; IMAGERECONSTRUCTION; EMISSION TOMOGRAPHY; EM ALGORITHM; BAYESIAN RECONSTRUCTION; SCATTER COMPENSATION; RESPONSE CORRECTION; DETECTOR RESPONSE; FEASIBLE IMAGES; LEASTSQUARES;
 Tipo documento:
 Article
 Natura:
 Periodico
 Settore Disciplinare:
 Clinical Medicine
 Engineering, Computing & Technology
 Citazioni:
 39
 Recensione:
 Indirizzi per estratti:
 Indirizzo: Lalush, DS Univ N Carolina, Dept Biomed Engn, Chapel Hill, NC 27599 USA Univ N Carolina Chapel Hill NC USA 27599 el Hill, NC 27599 USA



 Citazione:
 D.S. Lalush et al., "Fast maximum entropy approximation in SPECT using the RBIMAP algorithm", IEEE MED IM, 19(4), 2000, pp. 286294
Abstract
In this work, we present a method for approximating constrained maximum entropy (ME) reconstructions of SPECT data with modifications to a blockiterative maximum a posteriori (MAP) algorithm, Maximum likelihood (ML)based reconstruction algorithms require some form of noise smoothing. Constrained ME provides a more formal method of noise smoothing without requiring the user to select parameters. In the context of SPECT, constrained ME seeks theminimuminformation image estimate among those whose projections are a given distance from the noisy measured data, with that distance determined by the magnitude of the Poisson noise. Images that meet the distance criterionare referred to as feasible images, We find that modeling of all principaldegrading factors (attenuation, detector response, and scatter) in the reconstruction is critical because feasibility is not meaningful unless the projection model is as accurate as possible. Because the constrained ME solution is the same as a MAP solution for a particular value of the MAP weighting parameter, beta, the constrained ME solution can be found with a MAP algorithm if the correct value of beta is found. We show that the RBIMAP algorithm, if used with a dynamic scheme for estimating beta, can approximate constrained ME solutions in 20 or fewer iterations, We compare results for various methods of achieving feasible images on a simulation of Tl201 cardiac SPECT data. Results show that the RBIMAP ME approximation provides images and quantitative estimates close to those from a slower algorithm that gives the true ME solution, Also, we find that the ME results have higher spatial resolution and greater highfrequency noise content than a feasibilitybased stopping rule, feasibilitybased towpass filtering, and a quadratic Gibbs prior with beta selected according to the feasibility criterion. Weconclude that fast ME approximation is possible using either RBIMAP with the dynamic procedure or a feasibilitybased stopping rule, and that such reconstructions may be particularly useful in applications where resolution is critical.
ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 17/01/20 alle ore 20:39:35