Analytical Approach to Channelized Hotelling Observer Performance for Regularized Tomographic Image Reconstruction
dc.contributor.author | Yendiki, Anastasia | en_US |
dc.contributor.author | Fessler, Jeffrey A. | en_US |
dc.date.accessioned | 2011-08-18T18:21:13Z | |
dc.date.available | 2011-08-18T18:21:13Z | |
dc.date.issued | 2004-04-15 | en_US |
dc.identifier.citation | Yendiki, A.; Fessler, J.A. (2004). "Analytical Approach to Channelized Hotelling Observer Performance for Regularized Tomographic Image Reconstruction." IEEE International Symposium on Biomedical Imaging: Nano to Macro 1: 360-363. <http://hdl.handle.net/2027.42/85962> | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/85962 | |
dc.description.abstract | Our goal is to analyze regularized image reconstruction methods such as penalized likelihood with respect to the performance of the channelized Hotelling observer (CHO) in the task of detecting a small target signal in the reconstructed images, in the presence of a correlated random background. We derive here an approximation to the performance of the CHO by working entirely with continuous-space formulations and then discretizing the final result. This approach leads to an extension and a refinement of approximations that we previously derived in the discrete space. | en_US |
dc.publisher | IEEE | en_US |
dc.title | Analytical Approach to Channelized Hotelling Observer Performance for Regularized Tomographic 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 | Dept. of Electrical Engineering and Computer Science | en_US |
dc.identifier.pmid | 15248570 | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/85962/1/Fessler196.pdf | |
dc.identifier.doi | 10.1109/ISBI.2004.1398549 | en_US |
dc.identifier.source | IEEE International Symposium on Biomedical Imaging: Nano to Macro | 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.