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Volumn 48, Issue 2, 2009, Pages

Training set approach to smoothing parameter estimation for spline-regularized tomographic reconstruction

Author keywords

Bayesian methods; emission computed tomography; Gibbs priors; image reconstruction; smoothing parameter; spline energy

Indexed keywords

BAYESIAN APPROACHES; BAYESIAN METHODS; CLOSED-LOOP; EMISSION COMPUTED TOMOGRAPHY; GIBBS PRIORS; GIBBS SAMPLING; IMAGING APPLICATIONS; MATHEMATICAL PHANTOMS; NUMERICAL EXPERIMENTS; PERCENTAGE ERROR; PERFORMANCE OF ALGORITHM; PRIOR PROBABILITY; PROJECTION DATA; SMOOTHING PARAMETER; SMOOTHING PARAMETER ESTIMATION; TOMOGRAPHIC RECONSTRUCTION; TRAINING DATA; TRAINING SETS;

EID: 77949749285     PISSN: 00913286     EISSN: 15602303     Source Type: Journal    
DOI: 10.1117/1.3080742     Document Type: Article
Times cited : (3)

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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.