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Titolo:
BAYESIAN IMAGE-RECONSTRUCTION FOR EMISSION TOMOGRAPHY BASED ON MEDIANROOT PRIOR
Autore:
ALENIUS S; RUOTSALAINEN U;
Indirizzi:
TURKU PET CTR FIN-20520 TURKU FINLAND TURKU PET CTR FIN-20520 TURKU FINLAND TAMPERE UNIV TECHNOL,SIGNAL PROC LAB FIN-33101 TAMPERE FINLAND
Titolo Testata:
European journal of nuclear medicine
fascicolo: 3, volume: 24, anno: 1997,
pagine: 258 - 265
SICI:
0340-6997(1997)24:3<258:BIFETB>2.0.ZU;2-7
Fonte:
ISI
Lingua:
ENG
Soggetto:
EM ALGORITHM; GIBBS PRIORS; PERFORMANCE; MAXIMUM;
Keywords:
EMISSION TOMOGRAPHY; ITERATIVE BAYESIAN RECONSTRUCTION; POSITRON EMISSION TOMOGRAPHY; MAXIMUM LIKELIHOOD-EXPECTATION MAXIMIZATION; MEDIAN;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Science Citation Index Expanded
Citazioni:
15
Recensione:
Indirizzi per estratti:
Citazione:
S. Alenius e U. Ruotsalainen, "BAYESIAN IMAGE-RECONSTRUCTION FOR EMISSION TOMOGRAPHY BASED ON MEDIANROOT PRIOR", European journal of nuclear medicine, 24(3), 1997, pp. 258-265

Abstract

The aim of the present study was to investigate a new type of Bayesian one-step late reconstruction method which utilizes a median root prior (MRP). The method favours images which have locally monotonous radioactivity concentrations. The new reconstruction algorithm was appliedto ideal simulated data, phantom data and some patient examinations with PET, The same projection data were reconstructed with filtered back-projection (FBP) and maximum likelihood-expectation maximization (ML-EM) methods for comparison, The MRP method provided good-quality images with a similar resolution to the FBP method with a ramp filter, andat the same lime the noise properties were as good as with Hann-filtered FBP images. The typical artefacts seen in FBP reconstructed imagesoutside of the object were completely removed, as was the grainy noise inside the object, Quantitatively, the resulting average regional radioactivity concentrations in a large region of interest in images produced by the MRP method corresponded to the FBP and ML-EM results but st the pixel by pixel level the MRP method proved to be the most accurate of the tested methods. Tn contrast to other iterative reconstruction methods, e.g. ML-EMI the MRP method was not sensitive to the numberof iterations nor to the adjustment of reconstruction parameters. Only the Bayes lan parameter beta had to be set. The proposed MRP method is much more simple to calculate than the methods described previously, both with regard to the parameter settings and in terms of general use. The new MRP reconstruction method was shown to produce high-quality quantitative emission images with only one parameter setting in addition to the number of iterations.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 02/12/20 alle ore 14:48:25