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Title

An ordered-subsets proximal preconditioned gradient algorithm for edge-preserving PET image reconstruction
Authors
Mehranian, Abolfazl
Rahmim, Arman
Ay, Mohammad Reza
Kotasidis, Fotis
Zaidi, Habib
Published in Medical Physics. 2013, vol. 40, no. 5, p. 052503
Abstract In iterative positron emission tomography (PET) image reconstruction, the statistical variability of the PET data precorrected for random coincidences or acquired in sufficiently high count rates can be properly approximated by a Gaussian distribution, which can lead to a penalized weighted least-squares (PWLS) cost function. In this study, the authors propose a proximal preconditioned gradient algorithm accelerated with ordered subsets (PPG-OS) for the optimization of the PWLS cost function and develop a framework to incorporate boundary side information into edge-preserving total variation (TV) and Huber regularizations.
Keywords Algorithms — Brain/radionuclide imaging — Fluorodeoxyglucose F18/diagnostic use — Humans — Image Processing, Computer-Assisted/methods — Positron-Emission Tomography/methods
Identifiers
PMID: 23635293
Full text
Article (Published version) (1.5 MB) - document accessible for UNIGE members only Limited access to UNIGE
Structures
Faculté de médecine / Section de médecine clinique / Département de radiologie et informatique médicale
Research group Imagerie Médicale (TEP et TEMP) (542)
Project FNS: SNF 31003A-149957
Citation
(ISO format) 		MEHRANIAN, Abolfazl et al. An ordered-subsets proximal preconditioned gradient algorithm for edge-preserving PET image reconstruction. In: Medical Physics, 2013, vol. 40, n° 5, p. 052503. https://archive-ouverte.unige.ch/unige:40054

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Deposited on : 2014-09-09

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