Automatic Pharyngeal Phase Recognition in Untrimmed Videofluoroscopic Swallowing Study Using Transfer Learning with Deep Convolutional Neural Networks

Background: Video fluoroscopic swallowing study (VFSS) is considered as the gold standard diagnostic tool for evaluating dysphagia. However, it is time consuming and labor intensive for the clinician to manually search the recorded long video image frame by frame to identify the instantaneous swallo...

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Detalles Bibliográficos
Autores principales: Lee, Ki-Sun, Lee, Eunyoung, Choi, Bareun, Pyun, Sung-Bom
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7918932/
https://www.ncbi.nlm.nih.gov/pubmed/33668528
http://dx.doi.org/10.3390/diagnostics11020300

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7918932/
https://www.ncbi.nlm.nih.gov/pubmed/33668528
http://dx.doi.org/10.3390/diagnostics11020300

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