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dc.contributor.authorHoffmann, Malte
dc.contributor.authorAbaci Turk, Esra
dc.contributor.authorGagoski, Borjan
dc.contributor.authorMorgan, Leah
dc.contributor.authorWighton, Paul
dc.contributor.authorTisdall, Matthew Dylan
dc.contributor.authorReuter, Martin
dc.contributor.authorAdalsteinsson, Elfar
dc.contributor.authorGrant, Patricia Ellen
dc.contributor.authorWald, Lawrence L
dc.contributor.authorKouwe, André JW
dc.date.accessioned2022-05-24T18:04:26Z
dc.date.available2022-05-24T18:04:26Z
dc.date.issued2021
dc.identifier.urihttps://hdl.handle.net/1721.1/142675
dc.description.abstractIn fetal-brain MRI, head-pose changes between prescription and acquisition present a challenge to obtaining the standard sagittal, coronal and axial views essential to clinical assessment. As motion limits acquisitions to thick slices that preclude retrospective resampling, technologists repeat ~55-second stack-of-slices scans (HASTE) with incrementally reoriented field of view numerous times, deducing the head pose from previous stacks. To address this inefficient workflow, we propose a robust head-pose detection algorithm using full-uterus scout scans (EPI) which take ~5 seconds to acquire. Our ~2-second procedure automatically locates the fetal brain and eyes, which we derive from maximally stable extremal regions (MSERs). The success rate of the method exceeds 94% in the third trimester, outperforming a trained technologist by up to 20%. The pipeline may be used to automatically orient the anatomical sequence, removing the need to estimate the head pose from 2D views and reducing delays during which motion can occur.en_US
dc.language.isoen
dc.publisherWileyen_US
dc.relation.isversionof10.1002/IMA.22563en_US
dc.rightsCreative Commons Attribution 4.0 International Licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0en_US
dc.sourceWileyen_US
dc.titleRapid head‐pose detection for automated slice prescription of fetal‐brain MRIen_US
dc.typeArticleen_US
dc.identifier.citationHoffmann, Malte, Abaci Turk, Esra, Gagoski, Borjan, Morgan, Leah, Wighton, Paul et al. 2021. "Rapid head‐pose detection for automated slice prescription of fetal‐brain MRI." International Journal of Imaging Systems and Technology, 31 (3).
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.contributor.departmentMassachusetts Institute of Technology. Institute for Medical Engineering & Science
dc.relation.journalInternational Journal of Imaging Systems and Technologyen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2022-05-24T14:51:50Z
dspace.orderedauthorsHoffmann, M; Abaci Turk, E; Gagoski, B; Morgan, L; Wighton, P; Tisdall, MD; Reuter, M; Adalsteinsson, E; Grant, PE; Wald, LL; Kouwe, AJWen_US
dspace.date.submission2022-05-24T14:51:54Z
mit.journal.volume31en_US
mit.journal.issue3en_US
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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