Regularization for uniform spatial resolution properties in penalized-likelihood image reconstruction.
IEEE Trans Med Imaging
; 19(6): 601-15, 2000 Jun.
Article
em En
| MEDLINE
| ID: mdl-11026463
ABSTRACT
Traditional space-invariant regularization methods in tomographic image reconstruction using penalized-likelihood estimators produce images with nonuniform spatial resolution properties. The local point spread functions that quantify the smoothing properties of such estimators are space-variant, asymmetric, and object-dependent even for space-invariant imaging systems. We propose a new quadratic regularization scheme for tomographic imaging systems that yields increased spatial uniformity and is motivated by the least-squares fitting of a parameterized local impulse response to a desired global response. We have developed computationally efficient methods for PET systems with shift-invariant geometric responses. We demonstrate the increased spatial uniformity of this new method versus conventional quadratic regularization schemes in simulated PET thorax scans.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Tórax
/
Processamento de Imagem Assistida por Computador
/
Tomografia Computadorizada de Emissão
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
IEEE Trans Med Imaging
Ano de publicação:
2000
Tipo de documento:
Article