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학술대회 Detection of the Pharyngeal Phase in the Videofluoroscopic Swallowing Study Using Inflated 3D Convolutional Networks
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저자
이종택, 박은희
발행일
201809
출처
International Workshop on Machine Learning in Medical Imaging (MLMI) 2018 (LNCS 11046), pp.328-336
DOI
https://dx.doi.org/10.1007/978-3-030-00919-9_38
협약과제
18ZD1100, 대경권 지역산업 기반 ICT융합기술 고도화 지원사업, 문기영
초록
Videofluoroscopic swallowing study (VFSS) is a standard diagnostic tool for dysphagia. Previous computer assisted analysis of VFSS required manual preparation to mark several anatomical structures and to select time intervals of interest such as a pharyngeal phase during swallowing. These processes were still costly and challenging for clinicians. In this study, we present a novel approach to detect the pharyngeal phase of swallowing through whole of VFSS video clips using Inflated 3D Convolutional Networks (I3D) without additional manual annotations.
KSP 제안 키워드
3D convolutional networks, Computer Assisted Analysis, Diagnostic tool, Novel approach, Time interval, Video clips