ISWLS: Novel algorithm for image reconstruction in PET

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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.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

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