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

Karalis, E; Ortuno, J; Kontaxakis, G; Koutsouris, D

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	https://dspace.lib.ntua.gr/xmlui/handle/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