Model-based respiratory motion compensation for emission tomography image reconstruction.
Phys Med Biol
; 52(12): 3579-600, 2007 Jun 21.
Article
em En
| MEDLINE
| ID: mdl-17664561
ABSTRACT
In emission tomography imaging, respiratory motion causes artifacts in lungs and cardiac reconstructed images, which lead to misinterpretations, imprecise diagnosis, impairing of fusion with other modalities, etc. Solutions like respiratory gating, correlated dynamic PET techniques, list-mode data based techniques and others have been tested, which lead to improvements over the spatial activity distribution in lungs lesions, but which have the disadvantages of requiring additional instrumentation or the need of discarding part of the projection data used for reconstruction. The objective of this study is to incorporate respiratory motion compensation directly into the image reconstruction process, without any additional acquisition protocol consideration. To this end, we propose an extension to the maximum likelihood expectation maximization (MLEM) algorithm that includes a respiratory motion model, which takes into account the displacements and volume deformations produced by the respiratory motion during the data acquisition process. We present results from synthetic simulations incorporating real respiratory motion as well as from phantom and patient data.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Respiração
/
Algoritmos
/
Interpretação de Imagem Assistida por Computador
/
Tomografia Computadorizada de Emissão
Tipo de estudo:
Guideline
Limite:
Humans
Idioma:
En
Revista:
Phys Med Biol
Ano de publicação:
2007
Tipo de documento:
Article
País de afiliação:
França