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dc.contributor.authorWachinger, Christian
dc.contributor.authorGolland, Polina
dc.contributor.authorReuter, Martin
dc.contributor.authorWells, William M.
dc.date.accessioned2015-12-15T15:23:57Z
dc.date.available2015-12-15T15:23:57Z
dc.date.issued2014
dc.identifier.isbn978-3-319-10403-4
dc.identifier.isbn978-3-319-10404-1
dc.identifier.issn0302-9743
dc.identifier.issn1611-3349
dc.identifier.urihttp://hdl.handle.net/1721.1/100261
dc.description.abstractIntensity-based image registration requires resampling images on a common grid to evaluate the similarity function. The uncertainty of interpolation varies across the image, depending on the location of resampled points relative to the base grid. We propose to perform Bayesian inference with Gaussian processes, where the covariance matrix of the Gaussian process posterior distribution estimates the uncertainty in interpolation. The Gaussian process replaces a single image with a distribution over images that we integrate into a generative model for registration. Marginalization over resampled images leads to a new similarity measure that includes the uncertainty of the interpolation. We demonstrate that our approach increases the registration accuracy and propose an efficient approximation scheme that enables seamless integration with existing registration methods.en_US
dc.description.sponsorshipAlexander von Humboldt-Stiftungen_US
dc.description.sponsorshipNational Alliance for Medical Image Computing (U.S.) (U54-EB005149)en_US
dc.description.sponsorshipNeuroimaging Analysis Center (U.S.) (P41-EB015902)en_US
dc.description.sponsorshipNational Center for Image-Guided Therapy (U.S.) (P41-EB015898)en_US
dc.language.isoen_US
dc.publisherSpringer-Verlagen_US
dc.relation.isversionofhttp://dx.doi.org/10.1007/978-3-319-10404-1_34en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcePMCen_US
dc.titleGaussian Process Interpolation for Uncertainty Estimation in Image Registrationen_US
dc.typeArticleen_US
dc.identifier.citationWachinger, Christian, Polina Golland, Martin Reuter, and William Wells. “Gaussian Process Interpolation for Uncertainty Estimation in Image Registration.” Lecture Notes in Computer Science (2014): 267–274.en_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.mitauthorWachinger, Christianen_US
dc.contributor.mitauthorGolland, Polinaen_US
dc.contributor.mitauthorReuter, Martinen_US
dc.contributor.mitauthorWells, William M.en_US
dc.relation.journalMedical Image Computing and Computer-Assisted Intervention – MICCAI 2014en_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.orderedauthorsWachinger, Christian; Golland, Polina; Reuter, Martin; Wells, Williamen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-3652-1874
dc.identifier.orcidhttps://orcid.org/0000-0003-2516-731X
mit.licenseOPEN_ACCESS_POLICYen_US


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