On Complete-Data Spaces for PET Reconstruction Algorithms
dc.contributor.author | Fessler, Jeffrey A. | en_US |
dc.contributor.author | Clinthome, Neal H. | en_US |
dc.contributor.author | Rogers, W. Leslie | en_US |
dc.date.accessioned | 2011-08-18T18:20:52Z | |
dc.date.available | 2011-08-18T18:20:52Z | |
dc.date.issued | 1993-08 | en_US |
dc.identifier.citation | Fessler, J.A.; Clinthorne, N.H.; Rogers, W.L. (1993). "On Complete-Data Spaces for PET Reconstruction Algorithms". IEEE Transactions on Nuclear Science 40(4): 1055-1061. <http://hdl.handle.net/2027.42/85844> | en_US |
dc.identifier.issn | 0018-9499 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/85844 | |
dc.description.abstract | As investigators consider more comprehensive measurement models for emission tomography, there will be more choices for the complete-data spaces of the associated expectation-maximization algorithms for maximum-likelihood estimation. It is shown that EM algorithms based on smaller complete-data spaces will typically converge faster. Two practical applications of these concepts are discussed: the ML-IA and ML-IB image reconstruction algorithms of D.G. Politte and D.L. Snyder (1991) which are based on measurement models that account for attenuation and accidental coincidences in positron emission tomography (PET); and the problem of simultaneous estimation of emission and transmission parameters. Although the PET applications may often violate the necessary regularity conditions, the authors' analysis predicts heuristically that the ML-IB algorithm, which has a smaller complete-data space, should converge faster than ML-IA. | en_US |
dc.publisher | IEEE | en_US |
dc.title | On Complete-Data Spaces for PET Reconstruction Algorithms | 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 | Division of Nuclear Medicine. | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/85844/1/Fessler108.pdf | |
dc.identifier.doi | 10.1109/23.256712 | en_US |
dc.identifier.source | IEEE Transactions on Nuclear Science | en_US |
dc.owningcollname | Electrical Engineering and Computer Science, Department of (EECS) |
Files in this item
Remediation of Harmful Language
The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.
Accessibility
If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.