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dc.contributor.authorGrant, P. Ellen
dc.contributor.authorLiao, Ruizhi
dc.contributor.authorAbaci Turk, Esra
dc.contributor.authorZhang, Miaomiao
dc.contributor.authorLuo, Jie
dc.contributor.authorAdalsteinsson, Elfar
dc.contributor.authorGolland, Polina
dc.date.accessioned2016-10-28T14:46:15Z
dc.date.available2016-10-28T14:46:15Z
dc.date.issued2016-10
dc.identifier.urihttp://hdl.handle.net/1721.1/105124
dc.description.abstractWe present a robust method to correct for motion and deformations in in-utero volumetric MRI time series. Spatio-temporal analysis of dynamic MRI requires robust alignment across time in the presence of substantial and unpredictable motion. We make a Markov assumption on the nature of deformations to take advantage of the temporal structure in the image data. Forward message passing in the corresponding hidden Markov model (HMM) yields an estimation algorithm that only has to account for relatively small motion between consecutive frames. We demonstrate the utility of the temporal model by showing that its use improves the accuracy of the segmentation propagation through temporal registration. Our results suggest that the proposed model captures accurately the temporal dynamics of deformations in in-utero MRI time series.en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (NIH NIBIB NAC P41EB015902)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (NIH NICHD U01HD087211)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (NIH NIBIB R01EB017337)en_US
dc.description.sponsorshipWistron Corporationen_US
dc.description.sponsorshipMerrill Lynch Wealth Management (Fellowship)en_US
dc.language.isoen_US
dc.publisherMICCAI Societyen_US
dc.relation.isversionofhttp://www.miccai2016.org/files/downloads/MICCAI-2016-Program-Book.pdfen_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceLiaoen_US
dc.titleTemporal Registration in In-Utero Volumetric MRI Time Seriesen_US
dc.typeArticleen_US
dc.identifier.citationLiao, Ruizhi, Esra A. Turk, Miaomiao Zhang, Jie Luo, P. Ellen Grant, Elfar Adalsteinsson, and Polina Golland. "Temporal Registration in In-Utero Volumetric MRI Time Series." MICCA'16, 19th International Conference on Medical Image Computing & Computer Assisted Intervention, October 17-21, 2016, Athens, Greece.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.departmentMassachusetts Institute of Technology. Research Laboratory of Electronicsen_US
dc.contributor.approverLiao, Ruizhien_US
dc.contributor.mitauthorLiao, Ruizhi
dc.contributor.mitauthorAbaci Turk, Esra
dc.contributor.mitauthorZhang, Miaomiao
dc.contributor.mitauthorLuo, Jie
dc.contributor.mitauthorAdalsteinsson, Elfar
dc.contributor.mitauthorGolland, Polina
dc.relation.journal19th International Conference on Medical Image Computing & Computer Assisted Intervention, MICCAI'16en_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dspace.orderedauthorsLiao, Ruizhi; Turk, Esra A.; Zhang, Miaomiao; Luo, Jie; Grant, P. Ellen; Adalsteinsson, Elfar; Golland, Polinaen_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0001-6761-921X
dc.identifier.orcidhttps://orcid.org/0000-0003-0246-8793
dc.identifier.orcidhttps://orcid.org/0000-0002-0543-4778
dc.identifier.orcidhttps://orcid.org/0000-0002-7637-2914
dc.identifier.orcidhttps://orcid.org/0000-0003-2516-731X
mit.licenseOPEN_ACCESS_POLICYen_US


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