상세정보
학술대회
Detection of the Pharyngeal Phase in the Videofluoroscopic Swallowing Study Using Inflated 3D Convolutional Networks
- 저자
- 이종택, 박은희
- 발행일
- 201809
- 출처
- International Workshop on Machine Learning in Medical Imaging (MLMI) 2018 (LNCS 11046), pp.328-336
- 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