Quadratic Regularization Design for 3d Cylindrical PET

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dc.contributor.author Shi, Hugo en_US
dc.contributor.author Fessler, Jeffrey A. en_US
dc.date.accessioned 2011-08-18T18:20:55Z
dc.date.available 2011-08-18T18:20:55Z
dc.date.issued 2005-10-23 en_US
dc.identifier.citation Shi, H.; Fessier, J.A. (2005). "Quadratic Regularization Design for 3d Cylindrical PET." IEEE Nuclear Science Symposium Conference Record: 2301-2305. <http://hdl.handle.net/2027.42/85859> en_US
dc.identifier.uri http://hdl.handle.net/2027.42/85859
dc.description.abstract Statistical methods for tomographic image reconstruction lead to improved spatial resolution and noise properties in PET. Penalized-likelihood (PL) image reconstruction methods involve maximizing an objective function that is based on the log-likelihood of the sinogram measurements and on a roughness penalty function to control noise. In emission tomography, PL methods (and MAP methods) based on conventional quadratic regularization functions lead to nonuniform and anisotropic spatial resolution, even for idealized shift-invariant imaging systems. We have previously addressed this problem for parallel-beam 2D emission tomography, and for fan-beam 2D transmission tomography by designing data-dependent, shift-variant regularizers that improve resolution uniformity and isotropy, even for idealized shift-invariant imaging systems. This paper extends those methods to 3D cylindrical PET, using an analytical design approach that is numerically efficient. en_US
dc.publisher IEEE en_US
dc.title Quadratic Regularization Design for 3d Cylindrical PET en_US
dc.type article en_US
dc.subject.hlbsecondlevel Biomedical Engineering en_US
dc.subject.hlbtoplevel Engineering en_US
dc.description.peerreviewed Peer Reviewed en_US
dc.contributor.affiliationum Department of Electrical Engineering and Computer Science en_US
dc.description.bitstreamurl http://deepblue.lib.umich.edu/bitstream/2027.42/85859/1/Fessler212.pdf
dc.identifier.doi 10.1109/NSSMIC.2005.1596794 en_US
dc.identifier.source IEEE Nuclear Science Symposium Conference Record en_US
dc.owningcollname Electrical Engineering and Computer Science, Department of (EECS)
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