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Article: Diffeomorphic image registration of diffusion MRI using spherical harmonics

TitleDiffeomorphic image registration of diffusion MRI using spherical harmonics
Authors
KeywordsDiffeomorphisms
diffusion magnetic resonance imaging (MRI)
ODF reorientation
orientation distribution function (ODF)
registration
spherical harmonics
Issue Date2011
Citation
Ieee Transactions On Medical Imaging, 2011, v. 30 n. 3, p. 747-758 How to Cite?
AbstractNonrigid registration of diffusion magnetic resonance imaging (MRI) is crucial for group analyses and building white matter and fiber tract atlases. Most current diffusion MRI registration techniques are limited to the alignment of diffusion tensor imaging (DTI) data. We propose a novel diffeomorphic registration method for high angular resolution diffusion images by mapping their orientation distribution functions (ODFs). ODFs can be reconstructed using q-ball imaging (QBI) techniques and represented by spherical harmonics (SHs) to resolve intra-voxel fiber crossings. The registration is based on optimizing a diffeomorphic demons cost function. Unlike scalar images, deforming ODF maps requires ODF reorientation to maintain its consistency with the local fiber orientations. Our method simultaneously reorients the ODFs by computing a Wigner rotation matrix at each voxel, and applies it to the SH coefficients during registration. Rotation of the coefficients avoids the estimation of principal directions, which has no analytical solution and is time consuming. The proposed method was validated on both simulated and real data sets with various metrics, which include the distance between the estimated and simulated transformation fields, the standard deviation of the general fractional anisotropy and the directional consistency of the deformed and reference images. The registration performance using SHs with different maximum orders were compared using these metrics. Results show that the diffeomorphic registration improved the affine alignment, and registration using SHs with higher order SHs further improved the registration accuracy by reducing the shape difference and improving the directional consistency of the registered and reference ODF maps. © 2006 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/169880
ISSN
2015 Impact Factor: 3.756
2015 SCImago Journal Rankings: 1.941
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorGeng, Xen_HK
dc.contributor.authorRoss, TJen_HK
dc.contributor.authorGu, Hen_HK
dc.contributor.authorShin, Wen_HK
dc.contributor.authorZhan, Wen_HK
dc.contributor.authorChao, YPen_HK
dc.contributor.authorLin, CPen_HK
dc.contributor.authorSchuff, Nen_HK
dc.contributor.authorYang, Yen_HK
dc.date.accessioned2012-10-25T04:57:35Z-
dc.date.available2012-10-25T04:57:35Z-
dc.date.issued2011en_HK
dc.identifier.citationIeee Transactions On Medical Imaging, 2011, v. 30 n. 3, p. 747-758en_HK
dc.identifier.issn0278-0062en_HK
dc.identifier.urihttp://hdl.handle.net/10722/169880-
dc.description.abstractNonrigid registration of diffusion magnetic resonance imaging (MRI) is crucial for group analyses and building white matter and fiber tract atlases. Most current diffusion MRI registration techniques are limited to the alignment of diffusion tensor imaging (DTI) data. We propose a novel diffeomorphic registration method for high angular resolution diffusion images by mapping their orientation distribution functions (ODFs). ODFs can be reconstructed using q-ball imaging (QBI) techniques and represented by spherical harmonics (SHs) to resolve intra-voxel fiber crossings. The registration is based on optimizing a diffeomorphic demons cost function. Unlike scalar images, deforming ODF maps requires ODF reorientation to maintain its consistency with the local fiber orientations. Our method simultaneously reorients the ODFs by computing a Wigner rotation matrix at each voxel, and applies it to the SH coefficients during registration. Rotation of the coefficients avoids the estimation of principal directions, which has no analytical solution and is time consuming. The proposed method was validated on both simulated and real data sets with various metrics, which include the distance between the estimated and simulated transformation fields, the standard deviation of the general fractional anisotropy and the directional consistency of the deformed and reference images. The registration performance using SHs with different maximum orders were compared using these metrics. Results show that the diffeomorphic registration improved the affine alignment, and registration using SHs with higher order SHs further improved the registration accuracy by reducing the shape difference and improving the directional consistency of the registered and reference ODF maps. © 2006 IEEE.en_HK
dc.languageengen_US
dc.relation.ispartofIEEE Transactions on Medical Imagingen_HK
dc.subjectDiffeomorphismsen_HK
dc.subjectdiffusion magnetic resonance imaging (MRI)en_HK
dc.subjectODF reorientationen_HK
dc.subjectorientation distribution function (ODF)en_HK
dc.subjectregistrationen_HK
dc.subjectspherical harmonicsen_HK
dc.titleDiffeomorphic image registration of diffusion MRI using spherical harmonicsen_HK
dc.typeArticleen_HK
dc.identifier.emailGeng, X: gengx@hku.hken_HK
dc.identifier.authorityGeng, X=rp01678en_HK
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1109/TMI.2010.2095027en_HK
dc.identifier.pmid21134814-
dc.identifier.scopuseid_2-s2.0-79952126470en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-79952126470&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume30en_HK
dc.identifier.issue3en_HK
dc.identifier.spage747en_HK
dc.identifier.epage758en_HK
dc.identifier.isiWOS:000287862300018-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridGeng, X=34771310000en_HK
dc.identifier.scopusauthoridRoss, TJ=7203043487en_HK
dc.identifier.scopusauthoridGu, H=35233258000en_HK
dc.identifier.scopusauthoridShin, W=8573966900en_HK
dc.identifier.scopusauthoridZhan, W=7102238668en_HK
dc.identifier.scopusauthoridChao, YP=15843250800en_HK
dc.identifier.scopusauthoridLin, CP=35242710800en_HK
dc.identifier.scopusauthoridSchuff, N=7005417661en_HK
dc.identifier.scopusauthoridYang, Y=35294154700en_HK

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