Cited 26 times in
How does distortion correction correlate with anisotropic indices? A diffusion tensor imaging study
DC Field | Value | Language |
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dc.contributor.author | 김재진 | - |
dc.contributor.author | 박해정 | - |
dc.date.accessioned | 2015-06-10T12:47:58Z | - |
dc.date.available | 2015-06-10T12:47:58Z | - |
dc.date.issued | 2006 | - |
dc.identifier.issn | 0730-725X | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/110465 | - |
dc.description.abstract | PURPOSE: The purpose of this study was to determine a suitable registration algorithm for diffusion tensor imaging (DTI) using conventional preprocessing tools [statistical parametric mapping (SPM) and automated image registration (AIR)] and to investigate how anisotropic indices for clinical assessments are affected by these distortion corrections. MATERIALS AND METHODS: Brain DTI data from 15 normal healthy volunteers were used to evaluate four spatial registration schemes within subjects to correct image distortions: noncorrection, SPM-based affine registration, AIR-based affine registration and AIR-based nonlinear polynomial warping. The performance of each distortion correction was assessed using: (a) quantitative parameters: tensor-fitting error (Ef), mean dispersion index (MDI), mean fractional anisotropy (MFA) and mean variance (MV) within 11 regions of interest (ROI) defined from homogeneous fiber bundles; and (b) fiber tractography through the uncinate fasciculus and the corpus callosum. Fractional anisotropy (FA) and mean diffusivity (MD) were calculated to demonstrate the effects of distortion correction. Repeated-measures analysis of variance was used to investigate differences among the four registration paradigms. RESULTS: AIR-based nonlinear registration showed the best performance for reducing image distortions with respect to smaller Ef (P<.02), MDI (P<.01) and MV (P<.01) with larger MFA (P<.01). FA was decreased to correct distortions (P<.0001) whether the applied registration was linear or nonlinear and was lowest after nonlinear correction (P<.001). No significant differences were found in MD. CONCLUSION: In conventional DTI processing, anisotropic indices of FA can be misestimated by noncorrection or inappropriate distortion correction, which leads to an erroneous increase in FA. AIR-based nonlinear distortion correction would be required for a more accurate measurement of this diffusion parameter. | - |
dc.description.statementOfResponsibility | open | - |
dc.format.extent | 1369~1376 | - |
dc.relation.isPartOf | MAGNETIC RESONANCE IMAGING | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/2.0/kr/ | - |
dc.subject.MESH | Adult | - |
dc.subject.MESH | Algorithms | - |
dc.subject.MESH | Anisotropy | - |
dc.subject.MESH | Brain/metabolism* | - |
dc.subject.MESH | Diffusion Magnetic Resonance Imaging/methods* | - |
dc.subject.MESH | Humans | - |
dc.subject.MESH | Image Enhancement/methods* | - |
dc.subject.MESH | Image Processing, Computer-Assisted* | - |
dc.subject.MESH | Nonlinear Dynamics | - |
dc.title | How does distortion correction correlate with anisotropic indices? A diffusion tensor imaging study | - |
dc.type | Article | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.department | Dept. of Nuclear Medicine (핵의학) | - |
dc.contributor.googleauthor | Dae-Jin Kim | - |
dc.contributor.googleauthor | Hae-Jeong Park | - |
dc.contributor.googleauthor | Kyung-Whun Kang | - |
dc.contributor.googleauthor | Yong-Wook Shin | - |
dc.contributor.googleauthor | Jae-Jin Kim | - |
dc.contributor.googleauthor | Won-Jin Moon | - |
dc.contributor.googleauthor | Eun-Chul Chung | - |
dc.contributor.googleauthor | In Young Kim | - |
dc.contributor.googleauthor | Jun Soo Kwon | - |
dc.contributor.googleauthor | Sun I. Kim | - |
dc.identifier.doi | 10.1016/j.mri.2006.07.014 | - |
dc.admin.author | false | - |
dc.admin.mapping | false | - |
dc.contributor.localId | A00870 | - |
dc.contributor.localId | A01730 | - |
dc.relation.journalcode | J02178 | - |
dc.identifier.eissn | 1873-5894 | - |
dc.identifier.pmid | 17145409 | - |
dc.identifier.url | http://www.sciencedirect.com/science/article/pii/S0730725X06002451 | - |
dc.subject.keyword | Diffusion tensor imaging | - |
dc.subject.keyword | Distortion correction | - |
dc.subject.keyword | Image registration | - |
dc.subject.keyword | Evaluation | - |
dc.contributor.alternativeName | Kim, Jae Jin | - |
dc.contributor.alternativeName | Park, Hae Jeong | - |
dc.contributor.affiliatedAuthor | Kim, Jae Jin | - |
dc.contributor.affiliatedAuthor | Park, Hae Jeong | - |
dc.rights.accessRights | not free | - |
dc.citation.volume | 24 | - |
dc.citation.number | 10 | - |
dc.citation.startPage | 1369 | - |
dc.citation.endPage | 1376 | - |
dc.identifier.bibliographicCitation | MAGNETIC RESONANCE IMAGING, Vol.24(10) : 1369-1376, 2006 | - |
dc.identifier.rimsid | 39186 | - |
dc.type.rims | ART | - |
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