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Conference Paper
Detection of the Pharyngeal Phase in the Videofluoroscopic Swallowing Study Using Inflated 3D Convolutional Networks
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- Authors
- Jong Taek Lee, Eunhee Park
- Issue Date
- 2018-09
- Citation
- International Workshop on Machine Learning in Medical Imaging (MLMI) 2018 (LNCS 11046), pp.328-336
- Publisher
- Springer
- Language
- English
- Type
- Conference Paper
- Abstract
- 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 Keywords
- 3D convolutional networks, Computer Assisted Analysis, Diagnostic tool, Novel approach, Time interval, Video clips