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Conference Paper: Unbiased group-wise image registration: Applications in brain fiber tract atlas construction and functional connectivity analysis

TitleUnbiased group-wise image registration: Applications in brain fiber tract atlas construction and functional connectivity analysis
Authors
KeywordsDTI
Fiber tract
Fractional anisotropy
Group-wise image registration
Resting-state fMRI
Issue Date2011
PublisherSpringer New York LLC. The Journal's web site is located at http://springerlink.metapress.com/openurl.asp?genre=journal&issn=0148-5598
Citation
Journal of Medical Systems, 2011, v. 35 n. 5, p. 921-928 How to Cite?
AbstractWe propose an unbiased implicit-reference group-wise (IRG) image registration method and demonstrate its applications in the construction of a brain white matter fiber tract atlas and the analysis of resting-state functional MRI (fMRI) connectivity. Most image registration techniques pair-wise align images to a selected reference image and group analyses are performed in the reference space, which may produce bias. The proposed method jointly estimates transformations, with an elastic deformation model, registering all images to an implicit reference corresponding to the group average. The unbiased registration is applied to build a fiber tract atlas by registering a group of diffusion tensor images. Compared to reference-based registration, the IRG registration improves the fiber track overlap within the group. After applying the method in the fMRI connectivity analysis, results suggest a general improvement in functional connectivity maps at a group level in terms of larger cluster size and higher average t-scores. © 2010 US Government.
DescriptionThis journal issue entitled: Special Issue on Proceedings of the Second International Conference on Biomedical Engineering and Informatics, Special Issue on Distributed Diagnosis and Home Healthcare, Special Issue on ACM International Health Informatics 2010, Special Issue on Performance Measurement in the Health Sector and Special Issue on Ban on Healthcare Applications
Persistent Identifierhttp://hdl.handle.net/10722/169887
ISSN
2014 Impact Factor: 2.213
2015 SCImago Journal Rankings: 0.717
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorGeng, Xen_HK
dc.contributor.authorGu, Hen_HK
dc.contributor.authorShin, Wen_HK
dc.contributor.authorRoss, TJen_HK
dc.contributor.authorYang, Yen_HK
dc.date.accessioned2012-10-25T04:57:51Z-
dc.date.available2012-10-25T04:57:51Z-
dc.date.issued2011en_HK
dc.identifier.citationJournal of Medical Systems, 2011, v. 35 n. 5, p. 921-928en_US
dc.identifier.issn0148-5598en_HK
dc.identifier.urihttp://hdl.handle.net/10722/169887-
dc.descriptionThis journal issue entitled: Special Issue on Proceedings of the Second International Conference on Biomedical Engineering and Informatics, Special Issue on Distributed Diagnosis and Home Healthcare, Special Issue on ACM International Health Informatics 2010, Special Issue on Performance Measurement in the Health Sector and Special Issue on Ban on Healthcare Applications-
dc.description.abstractWe propose an unbiased implicit-reference group-wise (IRG) image registration method and demonstrate its applications in the construction of a brain white matter fiber tract atlas and the analysis of resting-state functional MRI (fMRI) connectivity. Most image registration techniques pair-wise align images to a selected reference image and group analyses are performed in the reference space, which may produce bias. The proposed method jointly estimates transformations, with an elastic deformation model, registering all images to an implicit reference corresponding to the group average. The unbiased registration is applied to build a fiber tract atlas by registering a group of diffusion tensor images. Compared to reference-based registration, the IRG registration improves the fiber track overlap within the group. After applying the method in the fMRI connectivity analysis, results suggest a general improvement in functional connectivity maps at a group level in terms of larger cluster size and higher average t-scores. © 2010 US Government.en_HK
dc.languageengen_US
dc.publisherSpringer New York LLC. The Journal's web site is located at http://springerlink.metapress.com/openurl.asp?genre=journal&issn=0148-5598en_HK
dc.relation.ispartofJournal of Medical Systemsen_HK
dc.subjectDTIen_HK
dc.subjectFiber tracten_HK
dc.subjectFractional anisotropyen_HK
dc.subjectGroup-wise image registrationen_HK
dc.subjectResting-state fMRIen_HK
dc.subject.meshAlgorithmsen_US
dc.subject.meshBrain - Anatomy & Histologyen_US
dc.subject.meshHumansen_US
dc.subject.meshImage Enhancementen_US
dc.subject.meshMagnetic Resonance Imagingen_US
dc.subject.meshNerve Fibers - Physiologyen_US
dc.subject.meshPattern Recognition, Automated - Methodsen_US
dc.titleUnbiased group-wise image registration: Applications in brain fiber tract atlas construction and functional connectivity analysisen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailGeng, X: gengx@hku.hken_HK
dc.identifier.authorityGeng, X=rp01678en_HK
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1007/s10916-010-9509-9en_HK
dc.identifier.pmid20703687-
dc.identifier.scopuseid_2-s2.0-84856224729en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-84856224729&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume35en_HK
dc.identifier.issue5en_HK
dc.identifier.spage921en_HK
dc.identifier.epage928en_HK
dc.identifier.isiWOS:000297856600022-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridGeng, X=34771310000en_HK
dc.identifier.scopusauthoridGu, H=35233258000en_HK
dc.identifier.scopusauthoridShin, W=8573966900en_HK
dc.identifier.scopusauthoridRoss, TJ=7203043487en_HK
dc.identifier.scopusauthoridYang, Y=7409387192en_HK
dc.identifier.citeulike7239244-
dc.customcontrol.immutablesml 160531 amended-

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