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dc.contributor.authorSIYEOP YOON-
dc.contributor.authorSon Jin Won-
dc.contributor.authorYoungjun Kim-
dc.contributor.authorPark, Se Hyung-
dc.contributor.authorLee, Deukhee-
dc.date.accessioned2024-01-12T06:13:51Z-
dc.date.available2024-01-12T06:13:51Z-
dc.date.created2021-09-29-
dc.date.issued2017-06-
dc.identifier.issn2325-033X-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/79514-
dc.description.abstractThe registration of preoperative 3D to intraoperative 2D images plays a crucial role in percutaneous coronary intervention. This technique reduces uncertainty regarding vessel topology and depth information in 2D intraoperative images. The aim of 2D/3D image registration is to determine the most appropriate image alignment. However, 2D/3D registration of heart images is challenging, due to differences in dimensionality and non-rigid motion, among others. In this paper, we propose a bifurcation-based biplane non-rigid 2D/3D registration method for coronary arteries. Experiments were performed in a virtual environment, and the results of the registration show an average distance with a ground truth of 0.57 mm.-
dc.languageEnglish-
dc.publisherKorea Robotics Society-
dc.subjectComputed tomography angiograph-
dc.subjectregistration-
dc.subjectcoronary artery-
dc.subjectX-ray-
dc.titleA study for non-rigid 2x2D-3D registration of coronary artery images using bifurcation points matching with bi-plane x-ray fluoroscopy-
dc.typeConference-
dc.description.journalClass1-
dc.identifier.bibliographicCitation14th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), pp.583 - 584-
dc.citation.title14th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)-
dc.citation.startPage583-
dc.citation.endPage584-
dc.citation.conferencePlaceKO-
dc.citation.conferencePlace제주-
dc.citation.conferenceDate2017-06-28-
dc.relation.isPartOf2017 14TH INTERNATIONAL CONFERENCE ON UBIQUITOUS ROBOTS AND AMBIENT INTELLIGENCE (URAI)-
dc.identifier.wosid000426976900150-
dc.identifier.scopusid2-s2.0-85034228127-
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KIST Conference Paper > 2017
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