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Quadratic Regularization Design for 2-D CT

dc.contributor.authorShi, Hugo R.en_US
dc.contributor.authorFessler, Jeffrey A.en_US
dc.date.accessioned2011-08-18T18:20:55Z
dc.date.available2011-08-18T18:20:55Z
dc.date.issued2008-10-31en_US
dc.identifier.citationShi, H.R. ; Fessler, J.A. (2009). "Quadratic Regularization Design for 2-D CT." IEEE Transactions on Medical Imaging 28(5): 645-656. <http://hdl.handle.net/2027.42/85858>en_US
dc.identifier.issn0278-0062en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/85858
dc.description.abstractStatistical methods for tomographic image reconstruction have improved noise and spatial resolution properties that may improve image quality in X-ray computed tomography (CT). Penalized weighted least squares (PWLS) methods using conventional quadratic regularization lead to nonuniform and anisotropic spatial resolution due to interactions between the weighting, which is necessary for good noise properties, and the regularizer. Previously, we addressed this problem for parallel-beam emission tomography using matrix algebra methods to design data-dependent, shift-variant regularizers that improve resolution uniformity. This paper develops a fast angular integral mostly analytical (AIMA) regularization design method for 2-D fan-beam X-ray CT imaging, for which parallel-beam tomography is a special case. Simulation results demonstrate that the new method for regularization design requires very modest computation and leads to nearly uniform and isotropic spatial resolution in transmission tomography when using quadratic regularization.en_US
dc.publisherIEEEen_US
dc.titleQuadratic Regularization Design for 2-D CTen_US
dc.typearticleen_US
dc.subject.hlbsecondlevelBiomedical Engineeringen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Electrical Engineering and Computer Science.en_US
dc.identifier.pmid19272993en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/85858/1/Fessler18.pdf
dc.identifier.doi10.1109/TMI.2008.2007366en_US
dc.identifier.sourceIEEE Transactions on Medical Imagingen_US
dc.owningcollnameElectrical Engineering and Computer Science, Department of (EECS)


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