In this work a new prior for variational Maximum a Posteriori regularization is proposed to be used in a 3D Time Of Flight (TOF) One-Step-Late (OSL) reconstruction algorithm which also accounts for the Point Spread Function (PSF) of the PET system. The new regularization prior is characterised by a strong smoothing component for background regions in the image, while preserving spatial resolution in signal regions. The new algorithm has been validated on phantom and clinical data. The results show an efficient compensation of noise as well as a good preservation of spatial resolution and quantitative accuracy

Rapisarda, E., Bettinardi, V., Presotto, L., Gilardi, M. (2012). Evaluation of a new regularization prior for 3D-OSEM PET reconstruction including PSF modelling. Intervento presentato a: GNB2012.

Evaluation of a new regularization prior for 3D-OSEM PET reconstruction including PSF modelling

RAPISARDA, EUGENIO;PRESOTTO, LUCA;GILARDI, MARIA CARLA
2012

Abstract

In this work a new prior for variational Maximum a Posteriori regularization is proposed to be used in a 3D Time Of Flight (TOF) One-Step-Late (OSL) reconstruction algorithm which also accounts for the Point Spread Function (PSF) of the PET system. The new regularization prior is characterised by a strong smoothing component for background regions in the image, while preserving spatial resolution in signal regions. The new algorithm has been validated on phantom and clinical data. The results show an efficient compensation of noise as well as a good preservation of spatial resolution and quantitative accuracy
poster + paper
Bayesian variational regularization; Point Spread Function; Image quality; Point Spread Function
English
GNB2012
2012
2012
none
Rapisarda, E., Bettinardi, V., Presotto, L., Gilardi, M. (2012). Evaluation of a new regularization prior for 3D-OSEM PET reconstruction including PSF modelling. Intervento presentato a: GNB2012.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/47858
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