Improved fMRI Time-Series Registration Using Joint Probability Density Priors
dc.contributor.author | Bhagalia, Roshni R. | en_US |
dc.contributor.author | Fessler, Jeffrey A. | en_US |
dc.contributor.author | Kim, Boklye | en_US |
dc.contributor.author | Meyer, Charles R. | en_US |
dc.date.accessioned | 2011-08-18T18:21:07Z | |
dc.date.available | 2011-08-18T18:21:07Z | |
dc.date.issued | 2009-02-08 | en_US |
dc.identifier.citation | Bhagalia, R.; Fessler, J. A.; Kim, B.; Meyer, C. R. (2009). "Improved fMRI Time-Series Registration Using Joint Probability Density Priors." Proc. Of SPIE. Medical Imaging: Image Processing 7259: 72590J:1-9. <http://hdl.handle.net/2027.42/85928> | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/85928 | |
dc.description.abstract | Functional MRI (fMRI) time-series studies are plagued by varying degrees of subject head motion. Faithful head motion correction is essential to accurately detect brain activation using statistical analyses of these time-series. Mutual information (MI) based slice-to-volume (SV) registration is used for motion estimation when the rate of change of head position is large. SV registration accounts for head motion between slice acquisitions by estimating an independent rigid transformation for each slice in the time-series. Consequently each MI optimization uses intensity counts from a single time-series slice, making the algorithm susceptible to noise for low complexity endslices (i.e., slices near the top of the head scans). This work focuses on improving the accuracy of MI-based SV registration of end-slices by using joint probability density priors derived from registered high complexity centerslices (i.e., slices near the middle of the head scans). Results show that the use of such priors can significantly improve SV registration accuracy. | en_US |
dc.publisher | SPIE | en_US |
dc.title | Improved fMRI Time-Series Registration Using Joint Probability Density Priors | 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. Department of Radiology | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/85928/1/Fessler236.pdf | |
dc.identifier.doi | 10.1117/12.811421 | en_US |
dc.identifier.source | Proc. Of SPIE. Medical Imaging: Image Processing | 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.