Motion Robust Magnetic Susceptibility and Field Inhomogeneity Estimation Using Regularized Image Restoration Techniques for fMRI
dc.contributor.author | Yeo, Desmond Teck Beng | en_US |
dc.contributor.author | Fessler, Jeffrey A. | en_US |
dc.contributor.author | Kim, Boklye | en_US |
dc.date.accessioned | 2011-08-18T18:21:10Z | |
dc.date.available | 2011-08-18T18:21:10Z | |
dc.date.issued | 2008-09-06 | en_US |
dc.identifier.citation | Yeo, D. T. B.; Fessler, J. A.; Kim, B. (2008). "Motion Robust Magnetic Susceptibility and Field Inhomogeneity Estimation Using Regularized Image Restoration Techniques for fMRI." Lecture Notes in Computer Science 5241: 991-998. <http://hdl.handle.net/2027.42/85944> | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/85944 | |
dc.description.abstract | In functional MRI, head motion may cause dynamic nonlinear field-inhomogeneity changes, especially with large out-of-plane rotations. This may lead to dynamic geometric distortion or blurring in the time series, which may reduce activation detection accuracy. The use of image registration to estimate dynamic field inhomogeneity maps from a static field map is not sufficient in the presence of such rotations. This paper introduces a retrospective approach to estimate magnetic susceptibility induced field maps of an object in motion, given a static susceptibility induced field map and the associated object motion parameters. It estimates a susceptibility map from a static field map using regularized image restoration techniques, and applies rigid body motion to the former. The dynamic field map is then computed using susceptibility voxel convolution. The method addresses field map changes due to out-of-plane rotations during time series acquisition and does not involve real time field map acquisitions. | en_US |
dc.publisher | Springer | en_US |
dc.title | Motion Robust Magnetic Susceptibility and Field Inhomogeneity Estimation Using Regularized Image Restoration Techniques for fMRI | 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 Radiology.Department of Electrical Engineering and Computer Science. | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/85944/1/Fessler233.pdf | |
dc.identifier.doi | 10.1007/978-3-540-85988-8_118 | en_US |
dc.identifier.source | Lecture Notes in Computer 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.