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dc.contributor.authorKim, Jin-
dc.contributor.authorLee, Hyesung-
dc.contributor.authorOh, Sang-Rok-
dc.contributor.authorYang, Sungwook-
dc.date.accessioned2024-02-29T01:30:33Z-
dc.date.available2024-02-29T01:30:33Z-
dc.date.created2024-02-29-
dc.date.issued2023-07-
dc.identifier.issn1557-170X-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/149348-
dc.description.abstractThis study presents a real-time sensor fusion framework based on the extended Kalman filter (EKF) for accurate and robust endomicroscopic image mosaicking. The sensor fusion framework incorporates an optical tracking system that can track 6-DOF pose of the imaging probe with high accuracy in real time in conjunction with 2D local image registration from image feature matching between two consecutive frames. We evaluated the performance of the real-time image mosaicking based on the sensor fusion compared with the image or tracker only approach. As a result, it could retain the microscopic level of image detail from the image-based approach and also achieve a robust image mosaic without any drift by using the accurate optical tracking system.-
dc.languageEnglish-
dc.publisherIEEE-
dc.titleReal-Time Endomicroscopic Image Mosaicking with an EKF-based Sensor Fusion Approach-
dc.typeConference-
dc.identifier.doi10.1109/EMBC40787.2023.10340903-
dc.description.journalClass1-
dc.identifier.bibliographicCitation45th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)-
dc.citation.title45th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)-
dc.citation.conferencePlaceUS-
dc.citation.conferencePlaceSydney, AUSTRALIA-
dc.citation.conferenceDate2023-07-24-
dc.relation.isPartOf2023 45TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE & BIOLOGY SOCIETY, EMBC-
dc.identifier.wosid001133788304018-
dc.identifier.scopusid2-s2.0-85179647388-
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KIST Conference Paper > 2023
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