New Deep Learning-Based Approach for Dysphagia Assessment from Videofluoroscopy Swallowing Studies-Reference-Cited by-同舟云学术

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New Deep Learning-Based Approach for Dysphagia Assessment from Videofluoroscopy Swallowing Studies

Published:2024-05-27 Issue: Volume: Page:1-4
ISSN:
Container-title:2024 IEEE International Symposium on Biomedical Imaging (ISBI)
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Author:

Cubero L.¹,Tessier C.²,Castelli J.¹,De Crevoisier R.¹,Jégoux F.²,Pascau J.³,Acosta O.¹

Affiliation:

1. Université Rennes,CLCC Eugène Marquis, Inserm,Rennes,France,F-35000

2. Université Rennes,Service d’ORL et Chirurgie Maxillo-Faciale, CHU Pontchaillou,Rennes,France,35033

3. Universidad Carlos III de Madrid,Departamento de Bioingeniería,Madrid,Spain

Funder

Instituto de Salud Carlos III

European Regional Development Fund

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10635099/10635102/10635369.pdf?arnumber=10635369

Reference10 articles.

1. Dysphagia Advances in Head and Neck Cancer

2. Evaluation of Objective and Subjective Swallowing Outcomes in Patients with Dysphagia Treated for Head and Neck Cancer

3. Deep Learning Analysis to Automatically Detect the Presence of Penetration or Aspiration in Videofluoroscopic Swallowing Study

4. Automated pharyngeal phase detection and bolus localization in videofluoroscopic swallowing study: Killing two birds with one stone?

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