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Iterative Image Reconstruction Methods applied to data from a prototype small-animal PET

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dc.contributor.author Karalis, E en
dc.contributor.author Ortuno, J en
dc.contributor.author Kontaxakis, G en
dc.contributor.author Koutsouris, D en
dc.date.accessioned 2014-03-01T02:50:58Z
dc.date.available 2014-03-01T02:50:58Z
dc.date.issued 2007 en
dc.identifier.uri http://hdl.handle.net/123456789/35258
dc.subject Cross Correlation en
dc.subject Evaluation Studies en
dc.subject Image Quality en
dc.subject Image Reconstruction en
dc.subject Iterative Reconstruction en
dc.subject Small Animal Pet en
dc.subject Visual Inspection en
dc.subject Contrast To Noise Ratio en
dc.subject Region of Interest en
dc.title Iterative Image Reconstruction Methods applied to data from a prototype small-animal PET en
heal.type conferenceItem en
heal.identifier.primary 10.1109/NEBC.2007.4413289 en
heal.identifier.secondary http://dx.doi.org/10.1109/NEBC.2007.4413289 en
heal.publicationDate 2007 en
heal.abstract The purpose of this study is to evaluate the average performance of algebraic and statistical iterative reconstruction methods, using phantom data from a prototype small-animal PET system. The algorithms that are being compared are the simultaneous versions of ART (SART) and MART (SMART), EM-ML, ISRA and WLS. The evaluation study was based on reconstructed image quality, as it is derived en
heal.journalName IEEE Annual Northeast Bioengineering Conference en
dc.identifier.doi 10.1109/NEBC.2007.4413289 en


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