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A Study of Four Minimization Approaches for Iterative Reconstruction in X-Ray CT
dc.contributor.authorDe Man, Brunoen_US
dc.contributor.authorBasu, Samiten_US
dc.contributor.authorThibault, Jean-Baptisteen_US
dc.contributor.authorHsieh, Jiangen_US
dc.contributor.authorFessler, Jeffrey A.en_US
dc.contributor.authorBouman, Charlesen_US
dc.contributor.authorSauer, Kenen_US
dc.date.accessioned2011-08-18T18:21:12Z
dc.date.available2011-08-18T18:21:12Z
dc.date.issued2005-10-23en_US
dc.identifier.citationDe Man, B.; Basu, S.; Thibault, J.-B.; Hsieh, J. ; Fessier, J.A.; Bouman, C.; Sauer, K. (2005). "A Study of Four Minimization Approaches for Iterative Reconstruction in X-Ray CT." IEEE Nuclear Science Symposium Conference Record: 2708-2710. <http://hdl.handle.net/2027.42/85952>en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/85952
dc.description.abstractThis paper compares four different minimization approaches for iterative reconstruction in CT:(1) iterative coordinate descent approach (ICD), (2) conjugate gradient approach (CG), (3) separable parabolic surrogate approach with ordered subsets (OS), and (4) convergent ordered subsets approach (COS). In addition to showing that all approaches result in the same final image, the paper gives an indication of the number of iterations and time to convergence for the studied approaches.en_US
dc.publisherIEEEen_US
dc.titleA Study of Four Minimization Approaches for Iterative Reconstruction in X-Ray CTen_US
dc.typearticleen_US
dc.subject.hlbsecondlevelBiomedical Engineeringen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationotherGE Global Res., Niskayuna, NY.en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/85952/1/Fessler210.pdf
dc.identifier.doi10.1109/NSSMIC.2005.1596895en_US
dc.identifier.sourceIEEE Nuclear Science Symposium Conference Recorden_US
dc.owningcollnameElectrical Engineering and Computer Science, Department of (EECS)


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