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dc.contributor.authorVan Leemput, Koen
dc.contributor.authorBakkour, Akram
dc.contributor.authorBenner, Thomas
dc.contributor.authorWiggins, Graham
dc.contributor.authorWald, Lawrence
dc.contributor.authorAugustinack, Jean
dc.contributor.authorDickerson, Bradford C.
dc.contributor.authorGolland, Polina
dc.contributor.authorFischl, Bruce
dc.date.accessioned2012-07-12T15:25:40Z
dc.date.available2012-07-12T15:25:40Z
dc.date.issued2009-05
dc.date.submitted2009-03
dc.identifier.issn1050-9631
dc.identifier.issn1098-1063
dc.identifier.urihttp://hdl.handle.net/1721.1/71591
dc.description.abstractRecent developments in MRI data acquisition technology are starting to yield images that show anatomical features of the hippocampal formation at an unprecedented level of detail, providing the basis for hippocampal subfield measurement. However, a fundamental bottleneck in MRI studies of the hippocampus at the subfield level is that they currently depend on manual segmentation, a laborious process that severely limits the amount of data that can be analyzed. In this article, we present a computational method for segmenting the hippocampal subfields in ultra-high resolution MRI data in a fully automated fashion. Using Bayesian inference, we use a statistical model of image formation around the hippocampal area to obtain automated segmentations. We validate the proposed technique by comparing its segmentations to corresponding manual delineations in ultra-high resolution MRI scans of 10 individuals, and show that automated volume measurements of the larger subfields correlate well with manual volume estimates. Unlike manual segmentations, our automated technique is fully reproducible, and fast enough to enable routine analysis of the hippocampal subfields in large imaging studies.en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (NIH NCRR; Grant number: P41-RR14075)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Grant R01 RR16594-01A1)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Grant NAC P41-RR13218)en_US
dc.description.sponsorshipBiomedical Informatics Research Network (BIRN002)en_US
dc.description.sponsorshipBiomedical Informatics Research Network (U24 RR021382)en_US
dc.description.sponsorshipNational Institute of Biomedical Imaging and Bioengineering (U.S.) (R01 EB001550)en_US
dc.description.sponsorshipNational Institute of Biomedical Imaging and Bioengineering (U.S.) (R01EB006758)en_US
dc.description.sponsorshipNational Institute of Biomedical Imaging and Bioengineering (U.S.) (NAMIC U54-EB005149)en_US
dc.description.sponsorshipNational Institute of Neurological Disorders and Stroke (U.S.) (R01 NS052585-01)en_US
dc.description.sponsorshipNational Institute of Neurological Disorders and Stroke (U.S.) (R01 NS051826)en_US
dc.description.sponsorshipMental Illness and Neuroscience Discovery (MIND) Instituteen_US
dc.description.sponsorshipEllison Medical Foundation (Autism & Dyslexia Project)en_US
dc.language.isoen_US
dc.publisherWiley-Blackwell Pubishersen_US
dc.relation.isversionofhttp://dx.doi.org/ 10.1002/hipo.20615en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alike 3.0en_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/en_US
dc.sourcePubMed Centralen_US
dc.titleAutomated Segmentation of Hippocampal Subfields From Ultra-High Resolution In Vivo MRIen_US
dc.typeArticleen_US
dc.identifier.citationVan Leemput, Koen et al. “Automated Segmentation of Hippocampal Subfields from Ultra-high Resolution in Vivo MRI.” Hippocampus 19.6 (2009): 549–557.en_US
dc.contributor.departmentHarvard University--MIT Division of Health Sciences and Technologyen_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.approverGolland, Polina
dc.contributor.mitauthorVan Leemput, Koen
dc.contributor.mitauthorWald, Lawrence
dc.contributor.mitauthorFischl, Bruce
dc.contributor.mitauthorGolland, Polina
dc.relation.journalHippocampusen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsVan Leemput, Koen; Bakkour, Akram; Benner, Thomas; Wiggins, Graham; Wald, Lawrence L.; Augustinack, Jean; Dickerson, Bradford C.; Golland, Polina; Fischl, Bruceen
dc.identifier.orcidhttps://orcid.org/0000-0003-2516-731X
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


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