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dc.contributor.authorCHAEWOO KIM-
dc.contributor.authorOGUZCAN BEKAR-
dc.contributor.authorHyunseok Seo-
dc.contributor.authorSang-Min Park-
dc.contributor.authorLee, Deukhee-
dc.date.accessioned2024-01-12T03:43:29Z-
dc.date.available2024-01-12T03:43:29Z-
dc.date.created2022-02-17-
dc.date.issued2021-12-10-
dc.identifier.issn--
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/77270-
dc.description.abstractAutomatic medical image segmentation is a crucial procedure in computer-aided surgery. However, the performance of automatic segmentation algorithms highly depends on the consistent properties of medical images. To address this issue, we propose a network for standardizing computed tomography (CT) images, aiming for the optimal performance of spine segmentation. We compare the synthesized and re-windowed images for performance assessment in terms of structural similarity and segmentation performance.-
dc.languageEnglish-
dc.publisherAACAS-
dc.subjectspine segmentation-
dc.subjectnull-
dc.subjectstandardization-
dc.subjectnull-
dc.subjectstyle transfer-
dc.titleComputed tomography vertebral segmentation from multi-vendor scanner data-
dc.typeConference-
dc.description.journalClass1-
dc.identifier.bibliographicCitationThe 17th Asian Conference on Computer Aided Surgery (ACCAS)-
dc.citation.titleThe 17th Asian Conference on Computer Aided Surgery (ACCAS)-
dc.citation.conferencePlaceKO-
dc.citation.conferencePlaceVirtual-
dc.citation.conferenceDate2021-12-10-
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KIST Conference Paper > 2021
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