Structure-aware Keypoint Localization for Videofluoroscopic Swallowing Study
Videofluoroscopic Swallowing Study (VFSS) is one of the gold standard for diagnosing swallowing disorders, providing dynamic X-ray imaging of the swallowing process.
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Key points
- Automated kinematic analysis in VFSS relies fundamentally on precise anatomical keypoint localization.
- However, existing studies focus on limited keypoints (e.g., cervical vertebrae or the hyoid) and overlook critical regions such as the soft palate, while annotating only active swallowing segments and ignoring abundant non-swallowing data, resulting in poor data efficiency.
- To tackle these challenges, we introduce VFSSKep, a novel dataset that extends annotations to the soft palate and incorporates large-scale unlabeled data.
- We further propose S$^3$KL, a Structure-aware Semi-Supervised Keypoint Localization framework designed to overcome spatial bias.
Sources (1)
- [1]Structure-aware Keypoint Localization for Videofluoroscopic Swallowing StudyarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 6, 04:21 AM
Videofluoroscopic Swallowing Study (VFSS) is one of the gold standard for diagnosing swallowing disorders, providing dynamic X-ray imaging of the swallowing process.
Automated kinematic analysis in VFSS relies fundamentally on precise anatomical keypoint localization.
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