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Segmentation-Free Statistical Image Reconstruction for Polyenergetic X-Ray Computed Tomography

dc.contributor.authorElbakri, Idris A.en_US
dc.contributor.authorFessler, Jeffrey A.en_US
dc.date.accessioned2011-08-18T18:20:59Z
dc.date.available2011-08-18T18:20:59Z
dc.date.issued2002-11-07en_US
dc.identifier.citationElbakri, I. A.; Fessler, J. A. (2002). "Segmentation-Free Statistical Image Reconstruction for Polyenergetic X-Ray Computed Tomography." International Symposium on Biomedical Imaging: 828-831. <http://hdl.handle.net/2027.42/85881>en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/85881
dc.description.abstractThis paper describes a statistical iterative reconstruction method for X-ray CT based on a physical model that accounts for the polyenergetic X-ray source spectrum and the measurement nonlinearities caused by energy-dependent attenuation. The algorithm accommodates mixtures of tissues with known mass attenuation coefficients but unknown densities. We formulate a penalized-likelihood approach for this polyenergetic model based on Poisson statistics.en_US
dc.publisherIEEEen_US
dc.titleSegmentation-Free Statistical Image Reconstruction for Polyenergetic X-Ray Computed Tomographyen_US
dc.typearticleen_US
dc.subject.hlbsecondlevelBiomedical Engineeringen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumElectrical Engineering and Computer Science Department.en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/85881/1/Fessler173.pdf
dc.identifier.doi10.1109/ISBI.2002.1029387en_US
dc.identifier.sourceInternational Symposium on Biomedical Imagingen_US
dc.owningcollnameElectrical Engineering and Computer Science, Department of (EECS)


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