Channelized Hotelling Observer Performance for Penalized-Likelihood Image Reconstruction
dc.contributor.author | Fessler, Jeffrey A. | en_US |
dc.contributor.author | Yendiki, Anastasia | en_US |
dc.date.accessioned | 2011-08-18T18:21:15Z | |
dc.date.available | 2011-08-18T18:21:15Z | |
dc.date.issued | 2002-11-10 | en_US |
dc.identifier.citation | Fessler, J.A.; Yendiki, A. (2002). "Channelized Hotelling Observer Performance for Penalized-Likelihood Image Reconstruction." IEEE Nuclear Science Symposium Conference Record 2: 1040-1044. <http://hdl.handle.net/2027.42/85971> | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/85971 | |
dc.description.abstract | What type of regularization method is optimal for penalized-likelihood image reconstruction when the imaging task is signal detection based on a channelized Hotelling (CHO) observer? To answer such questions, one would like to have a simple analytical expression (even if approximate) for the performance (SNR) of the CHO observer given different reconstruction methods. Bonetto, Qi, and Leahy (IEEE T-NS, Aug. 2000) derived and validated one such expression for penalized-likelihood (aka MAP) reconstruction and the Signal Known Exactly (SKE) problem using linearizations and local shift-invariance approximations. This paper describes a further simplification of the analytical SNR expression for the more general case of a Gaussian-distributed signal. This simplification, based on frequency-domain decompositions, greatly reduces computation time and thus can facilitate analytical comparisons between reconstruction methods in the context of detection tasks. It also leads to the very interesting result that regularization is not essential in this context for a large family of linear observers. | en_US |
dc.publisher | IEEE | en_US |
dc.title | Channelized Hotelling Observer Performance for Penalized-Likelihood Image Reconstruction | 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/2027.42/85971/1/Fessler177.pdf | |
dc.identifier.doi | 10.1109/NSSMIC.2002.1239500 | en_US |
dc.identifier.source | IEEE Nuclear Science Symposium Conference Record | 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.