Spatial Resolution and Noise Properties of Regularized Motion-Compensated Image Reconstruction
dc.contributor.author | Chun, So Young | en_US |
dc.contributor.author | Fessler, Jeffrey A. | en_US |
dc.date.accessioned | 2011-08-18T18:21:00Z | |
dc.date.available | 2011-08-18T18:21:00Z | |
dc.date.issued | 2009-06-28 | en_US |
dc.identifier.citation | Chun, S. Y.; Fessler, J.A. (2009). "Spatial Resolution and Noise Properties of Regularized Motion-Compensated Image Reconstruction ." IEEE International Symposium on Biomedical Imaging: From Nano to Macro: 863-866. <http://hdl.handle.net/2027.42/85889> | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/85889 | |
dc.description.abstract | Reducing motion artifacts is an important problem in medical image reconstruction. Using gating to partition data into separate frames can reduce motion artifacts but can increase noise in images reconstructed from individual frames. One can pool the frames to reduce noise by using motion-compensated image reconstruction (MCIR) methods. MCIR methods have been studied in many medical imaging modalities to reduce both noise and motion artifacts. However, there has been less analysis of the spatial resolution and noise properties of MCIR methods. This paper analyzes the spatial resolution and noise properties of MCIR methods based on a general parametric motion model. For simplicity we consider the motion to be given. We present a method to choose quadratic spatial regularization parameters to provide predictable resolution properties that are independent of the object and the motion. The noise analysis shows that the estimator variance depends on both the measurement covariance and the Jacobian determinant values of the motion. A 2D PET simulation demonstrates the theoretical results. | en_US |
dc.publisher | IEEE | en_US |
dc.title | Spatial Resolution and Noise Properties of Regularized Motion-Compensated 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 | Electrical Engineering and Computer Science. | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/85889/1/Fessler240.pdf | |
dc.identifier.doi | 10.1109/ISBI.2009.5193189 | en_US |
dc.identifier.source | IEEE International Symposium on Biomedical Imaging: From 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.