21346272

Source:http://linkedlifedata.com/resource/pubmed/id/21346272

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Predicate	Object
rdf:type	pubmed:Citation
lifeskim:mentions	umls-concept:C0000894, umls-concept:C0002045, umls-concept:C0031268, umls-concept:C0032743, umls-concept:C0524865, umls-concept:C1514811, umls-concept:C1533716, umls-concept:C1561577, umls-concept:C1705176, umls-concept:C1705178, umls-concept:C1706462
pubmed:issue	6
pubmed:dateCreated	2011-3-2
pubmed:abstractText	Patient motion during positron emission tomography scans leads to significant resolution loss and image degradation. Motion-compensated image reconstruction (MCIR) algorithms have proven to be reliable correction methods given accurate deformation fields. However, although ordered subsets (OS) are widely used to speed up the convergence, OS-MCIR algorithms are still computationally expensive. This study concentrates on acceleration of OS-MCIR algorithms through two methods: combining OS with motion subsets and use of an initial estimate based on reference gate data. These approaches were compared to two existing OS-MCIR algorithms and post-reconstruction registration using data from the NCAT phantom. The methods were evaluated in terms of noise, lesion bias and contrast-to-noise ratio (CNR). The straightforward combination of motion subsets with projection subsets (OSGEM) produced inferior results (lower CNR, p < 0.01) to existing OS-MCIR algorithms. The addition of a spacer step using data from all gates to OSGEM resulted in an algorithm (SS-OSGEM) that generated images that were statistically consistent with those from existing OS-MCIR algorithms (no significant difference in CNR, p > 0.05) at one third of the computational expense. The use of a reference gate initial estimate (MCDOi) resulted in comparable image quality in terms of bias and CNR (p > 0.05) at half the computational burden. This study indicates that MCDOi and SS-OSGEM in particular are attractive accelerated OS-MCIR approaches.
pubmed:language	eng
pubmed:journal	http://linkedlifedata.com/resource/pubmed/journal/0401220
pubmed:citationSubset	IM
pubmed:status	MEDLINE
pubmed:month	Mar
pubmed:issn	1361-6560
pubmed:author	pubmed-author:DikaiosNN, pubmed-author:FryerT DTD
pubmed:issnType	Electronic
pubmed:day	21
pubmed:volume	56
pubmed:owner	NLM
pubmed:authorsComplete	Y
pubmed:pagination	1695-715
pubmed:meshHeading	pubmed-meshheading:21346272-Acceleration, pubmed-meshheading:21346272-Algorithms, pubmed-meshheading:21346272-Humans, pubmed-meshheading:21346272-Image Processing, Computer-Assisted, pubmed-meshheading:21346272-Liver, pubmed-meshheading:21346272-Lung, pubmed-meshheading:21346272-Motion, pubmed-meshheading:21346272-Phantoms, Imaging, pubmed-meshheading:21346272-Positron-Emission Tomography, pubmed-meshheading:21346272-Reproducibility of Results
pubmed:year	2011
pubmed:articleTitle	Acceleration of motion-compensated PET reconstruction: ordered subsets-gates EM algorithms and a priori reference gate information.
pubmed:affiliation	Department of Clinical Neurosciences, Wolfson Brain Imaging Centre, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK.
pubmed:publicationType	Journal Article, Research Support, Non-U.S. Gov't