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dc.contributor.authorXu, Junshen
dc.contributor.authorAbaci Turk, Esra
dc.contributor.authorGrant, P Ellen
dc.contributor.authorGolland, Polina
dc.contributor.authorAdalsteinsson, Elfar
dc.date.accessioned2022-05-24T14:52:15Z
dc.date.available2022-05-24T14:52:15Z
dc.date.issued2021
dc.identifier.urihttps://hdl.handle.net/1721.1/142674
dc.language.isoen
dc.publisherSpringer International Publishingen_US
dc.relation.isversionof10.1007/978-3-030-87234-2_19en_US
dc.rightsCreative Commons Attribution-NonCommercial-ShareAlike 4.0 Internationalen_US
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcearXiven_US
dc.titleSTRESS: Super-Resolution for Dynamic Fetal MRI Using Self-supervised Learningen_US
dc.typeArticleen_US
dc.identifier.citationXu, Junshen, Abaci Turk, Esra, Grant, P Ellen, Golland, Polina and Adalsteinsson, Elfar. 2021. "STRESS: Super-Resolution for Dynamic Fetal MRI Using Self-supervised Learning." MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2021, PT VII, 12907.
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
dc.contributor.departmentMassachusetts Institute of Technology. Institute for Medical Engineering & Science
dc.relation.journalMEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2021, PT VIIen_US
dc.eprint.versionOriginal manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2022-05-24T14:42:44Z
dspace.orderedauthorsXu, J; Abaci Turk, E; Grant, PE; Golland, P; Adalsteinsson, Een_US
dspace.date.submission2022-05-24T14:42:45Z
mit.journal.volume12907en_US
mit.licenseOPEN_ACCESS_POLICY
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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