Gradient nonlinearity calibration and correction for a compact, asymmetric magnetic resonance imaging gradient system
DC Field | Value | Language |
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dc.contributor.author | S Tao | - |
dc.contributor.author | J D Trzasko | - |
dc.contributor.author | J L Gunter | - |
dc.contributor.author | P T Weavers | - |
dc.contributor.author | Y Shu | - |
dc.contributor.author | J Huston III | - |
dc.contributor.author | Seung-Kyun Lee | - |
dc.contributor.author | E T Tan | - |
dc.contributor.author | M A Bernstein | - |
dc.date.available | 2017-09-05T05:35:16Z | - |
dc.date.created | 2017-02-24 | - |
dc.date.issued | 2017-01 | - |
dc.identifier.issn | 0031-9155 | - |
dc.identifier.uri | https://pr.ibs.re.kr/handle/8788114/3773 | - |
dc.description.abstract | Due to engineering limitations, the spatial encoding gradient fields in conventional magnetic resonance imaging cannot be perfectly linear and always contain higher-order, nonlinear components. If ignored during image reconstruction, gradient nonlinearity (GNL) manifests as image geometric distortion. Given an estimate of the GNL field, this distortion can be corrected to a degree proportional to the accuracy of the field estimate. The GNL of a gradient system is typically characterized using a spherical harmonic polynomial model with model coefficients obtained from electromagnetic simulation. Conventional whole-body gradient systems are symmetric in design; typically, only odd-order terms up to the 5th-order are required for GNL modeling. Recently, a high-performance, asymmetric gradient system was developed, which exhibits more complex GNL that requires higher-order terms including both odd-and even-orders for accurate modeling. This work characterizes the GNL of this system using an iterative calibration method and a fiducial phantom used in ADNI (Alzheimer's Disease Neuroimaging Initiative). The phantom was scanned at different locations inside the 26 cm diameter-spherical-volume of this gradient, and the positions of fiducials in the phantom were estimated. An iterative calibration procedure was utilized to identify the model coefficients that minimize the mean-squared-error between the true fiducial positions and the positions estimated from images corrected using these coefficients. To examine the effect of higher-order and even-order terms, this calibration was performed using spherical harmonic polynomial of different orders up to the 10th-order including even- and odd-order terms, or odd-order only. The results showed that the model coefficients of this gradient can be successfully estimated. The residual root-mean-squared-error after correction using up to the 10th-order coefficients was reduced to 0.36 mm, yielding spatial accuracy comparable to conventional whole-body gradients. The even-order terms were necessary for accurate GNL modeling. In addition, the calibrated coefficients improved image geometric accuracy compared with the simulation-based coefficients. © 2016 Institute of Physics and Engineering in Medicine Printed in the UK | - |
dc.description.uri | 1 | - |
dc.language | 영어 | - |
dc.publisher | IOP PUBLISHING LTD | - |
dc.subject | gradient nonlinearity | - |
dc.subject | image geometric distortion | - |
dc.subject | asymmetric gradient | - |
dc.subject | head-only MRI system | - |
dc.subject | compact 3T | - |
dc.title | Gradient nonlinearity calibration and correction for a compact, asymmetric magnetic resonance imaging gradient system | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.identifier.wosid | 000391749200001 | - |
dc.identifier.scopusid | 2-s2.0-85010064965 | - |
dc.identifier.rimsid | 58804 | ko |
dc.date.tcdate | 2018-10-01 | - |
dc.contributor.affiliatedAuthor | Seung-Kyun Lee | - |
dc.identifier.doi | 10.1088/1361-6560/aa524f | - |
dc.identifier.bibliographicCitation | PHYSICS IN MEDICINE AND BIOLOGY, v.62, no.2, pp.N18 - N31 | - |
dc.citation.title | PHYSICS IN MEDICINE AND BIOLOGY | - |
dc.citation.volume | 62 | - |
dc.citation.number | 2 | - |
dc.citation.startPage | N18 | - |
dc.citation.endPage | N31 | - |
dc.date.scptcdate | 2018-10-01 | - |
dc.description.wostc | 2 | - |
dc.description.scptc | 4 | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordPlus | GEOMETRIC DISTORTION | - |
dc.subject.keywordPlus | MR-IMAGES | - |
dc.subject.keywordPlus | PHANTOM | - |
dc.subject.keywordPlus | RELIABILITY | - |
dc.subject.keywordPlus | PERFORMANCE | - |
dc.subject.keywordPlus | EXPERIENCE | - |
dc.subject.keywordPlus | SEQUENCE | - |
dc.subject.keywordPlus | ADNI | - |
dc.subject.keywordAuthor | gradient nonlinearity | - |
dc.subject.keywordAuthor | image geometric distortion | - |
dc.subject.keywordAuthor | asymmetric gradient | - |
dc.subject.keywordAuthor | head-only MRI system | - |
dc.subject.keywordAuthor | compact 3T | - |