ISWLS: Novel algorithm for image reconstruction in PET

Karali, E; Pavlopoulos, S; Lambropoulou, S; Koutsouris, D

dc.contributor.author	Karali, E	en
dc.contributor.author	Pavlopoulos, S	en
dc.contributor.author	Lambropoulou, S	en
dc.contributor.author	Koutsouris, D	en
dc.date.accessioned	2014-03-01T01:35:54Z
dc.date.available	2014-03-01T01:35:54Z
dc.date.issued	2011	en
dc.identifier.issn	1089-7771	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/21245
dc.subject	Image reconstruction	en
dc.subject	positron emission tomography (PET)	en
dc.subject	small-animal imaging	en
dc.subject.classification	Computer Science, Information Systems	en
dc.subject.classification	Computer Science, Interdisciplinary Applications	en
dc.subject.classification	Mathematical & Computational Biology	en
dc.subject.classification	Medical Informatics	en
dc.subject.other	Algebraic reconstruction techniques	en
dc.subject.other	Contrast to noise ratio	en
dc.subject.other	Cross-correlation coefficient	en
dc.subject.other	Different sizes	en
dc.subject.other	Expectation Maximization	en
dc.subject.other	Image space	en
dc.subject.other	Iterative algorithm	en
dc.subject.other	Medical image reconstruction	en
dc.subject.other	Novel algorithm	en
dc.subject.other	Ordered subsets	en
dc.subject.other	Phantom data	en
dc.subject.other	Reconstruction process	en
dc.subject.other	Simultaneous algebraic reconstruction technique	en
dc.subject.other	Sinograms	en
dc.subject.other	Small-animal	en
dc.subject.other	small-animal imaging	en
dc.subject.other	Weighted least squares	en
dc.subject.other	Algebra	en
dc.subject.other	Algorithms	en
dc.subject.other	Animals	en
dc.subject.other	Electrons	en
dc.subject.other	Image reconstruction	en
dc.subject.other	Iterative methods	en
dc.subject.other	Maximum likelihood	en
dc.subject.other	Medical imaging	en
dc.subject.other	Positrons	en
dc.subject.other	Positron emission tomography	en
dc.title	ISWLS: Novel algorithm for image reconstruction in PET	en
heal.type	journalArticle	en
heal.identifier.primary	10.1109/TITB.2010.2104161	en
heal.identifier.secondary	http://dx.doi.org/10.1109/TITB.2010.2104161	en
heal.identifier.secondary	5680967	en
heal.language	English	en
heal.publicationDate	2011	en
heal.abstract	The purpose of this study is to introduce a novel empirical iterative algorithm for medical image reconstruction, under the short name ISWLS (image space weighted least squares), which is expected to have image space reconstruction algorithm (ISRA) properties in noise manipulation and weighted least-squares (WLS) acceleration of the reconstruction process. We used phantom data from a prototype small-animal positron emission tomography system and the methods presented here are applied to 2-D sinograms. Further, we assess the performance of the new algorithm by comparing it to the simultaneous version of algebraic reconstruction technique (ART), simultaneous algebraic reconstruction technique (SART), to expectation maximization maximum likelihood (EM-ML), ISRA, and WLS. All algorithms are compared in terms of cross-correlation coefficient, reconstruction time, and contrast-to-noise ratios (CNRs). As it turns out, ISWLS presents higher CNRs than EM-ML, ISRA, and SART for objects of different sizes. Also, ISWLS shows similar performance to WLS during the first iterations but it has better noise manipulation. Finally, ordered subsets ISWLS (OS-ISWLS), the OS version of ISWLS, shows its best performance between the first six-nine iterations. Its behavior seems to be a compromise between OS-ISRA and OS-WLS. © 2011 IEEE.	en
heal.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC	en
heal.journalName	IEEE Transactions on Information Technology in Biomedicine	en
dc.identifier.doi	10.1109/TITB.2010.2104161	en
dc.identifier.isi	ISI:000290170300005	en
dc.identifier.volume	15	en
dc.identifier.issue	3	en
dc.identifier.spage	381	en
dc.identifier.epage	386	en