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dc.contributor.author김명희-
dc.date.accessioned2018-06-02T08:15:08Z-
dc.date.available2018-06-02T08:15:08Z-
dc.date.issued1997-
dc.identifier.issn0278-0062-
dc.identifier.otherOAK-17027-
dc.identifier.urihttps://dspace.ewha.ac.kr/handle/2015.oak/244410-
dc.description.abstractA number of segmentation algorithms have been developed, but those algorithms are not effective on volume reconstruction because they are limited to operating only on two-dimensional (2-D) images. In this paper, we propose the volumetric object reconstruction method using the three-dimensional Markov random field (3D-MRF) model-based segmentation. The 3D-MRF model is known to be one of efficient ways to model spatial contextual information. The method is compared with the 2-D region growing scheme under three types of interpolation. The results show that the proposed method is better in the aspect of image quality than other methods. © 1997 IEEE.-
dc.languageEnglish-
dc.titleVolumetric object reconstruction using the 3D-MRF model-based segmentation-
dc.typeArticle-
dc.relation.issue6-
dc.relation.volume16-
dc.relation.indexSCIE-
dc.relation.indexSCOPUS-
dc.relation.startpage887-
dc.relation.lastpage892-
dc.relation.journaltitleIEEE Transactions on Medical Imaging-
dc.identifier.scopusid2-s2.0-0031283419-
dc.author.googleChoi S.M.-
dc.author.googleLee J.E.-
dc.author.googleKim J.-
dc.author.googleKim M.H.-
dc.contributor.scopusid김명희(34770838100)-
dc.date.modifydate20180601100925-
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엘텍공과대학 > 컴퓨터공학과 > Journal papers
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