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dc.contributor.author장동표-
dc.date.accessioned2019-11-24T14:44:27Z-
dc.date.available2019-11-24T14:44:27Z-
dc.date.issued2017-04-
dc.identifier.citationDYSPHAGIA, v. 32, no. 2, page. 315-326en_US
dc.identifier.issn0179-051X-
dc.identifier.issn1432-0460-
dc.identifier.urihttps://link.springer.com/article/10.1007%2Fs00455-016-9759-x-
dc.identifier.urihttps://repository.hanyang.ac.kr/handle/20.500.11754/113701-
dc.description.abstractConventional kinematic analysis of videofluoroscopic (VF) swallowing image, most popular for dysphagia diagnosis, requires time-consuming and repetitive manual extraction of diagnostic information from multiple images representing one swallowing period, which results in a heavy work load for clinicians and excessive hospital visits for patients to receive counseling and prescriptions. In this study, a software platform was developed that can assist in the VF diagnosis of dysphagia by automatically extracting a two-dimensional moving trajectory of the hyoid bone as well as 11 temporal and kinematic parameters. Fifty VF swallowing videos containing both non-mandible-overlapped and mandible-overlapped cases from eight patients with dysphagia of various etiologies and 19 videos from ten healthy controls were utilized for performance verification. Percent errors of hyoid bone tracking were 1.7 +/- 2.1% for non-overlapped images and 4.2 +/- 4.8% for overlapped images. Correlation coefficients between manually extracted and automatically extracted moving trajectories of the hyoid bone were 0.986 +/- 0.017 (X-axis) and 0.992 +/- 0.006 (Y-axis) for non-overlapped images, and 0.988 +/- 0.009 (X-axis) and 0.991 +/- 0.006 (Y-axis) for overlapped images. Based on the experimental results, we believe that the proposed platform has the potential to improve the satisfaction of both clinicians and patients with dysphagia.en_US
dc.description.sponsorshipThis research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (NRF-2013R1A1A1004622 and NRF-2015R1D1A1A01058652).en_US
dc.language.isoen_USen_US
dc.publisherSPRINGERen_US
dc.subjectDysphagiaen_US
dc.subjectVideofluoroscopicen_US
dc.subjectHyoid boneen_US
dc.subjectDiagnosisen_US
dc.subjectDeglutitionen_US
dc.subjectDeglutition disordersen_US
dc.titleA Supporting Platform for Semi-Automatic Hyoid Bone Tracking and Parameter Extraction from Videofluoroscopic Images for the Diagnosis of Dysphagia Patientsen_US
dc.typeArticleen_US
dc.relation.no2-
dc.relation.volume32-
dc.identifier.doi10.1007/s00455-016-9759-x-
dc.relation.page315-326-
dc.relation.journalDYSPHAGIA-
dc.contributor.googleauthorLee, Jun Chang-
dc.contributor.googleauthorNam, Kyoung Won-
dc.contributor.googleauthorJang, Dong Pyo-
dc.contributor.googleauthorPaik, Nam Jong-
dc.contributor.googleauthorRyu, Ju Seok-
dc.contributor.googleauthorKim, In Young-
dc.relation.code2017001341-
dc.sector.campusS-
dc.sector.daehakGRADUATE SCHOOL OF BIOMEDICAL SCIENCE AND ENGINEERING[S]-
dc.identifier.piddongpjang-
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