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A Deep Learning Approach for Quantifying Vocal Fold Dynamics During Connected Speech Using Laryngeal High-Speed Videoendoscopy.
Yousef, Ahmed M; Deliyski, Dimitar D; Zacharias, Stephanie R C; de Alarcon, Alessandro; Orlikoff, Robert F; Naghibolhosseini, Maryam.
Affiliation
  • Yousef AM; Department of Communicative Sciences and Disorders, Michigan State University, East Lansing.
  • Deliyski DD; Department of Communicative Sciences and Disorders, Michigan State University, East Lansing.
  • Zacharias SRC; Head and Neck Regenerative Medicine Program, Mayo Clinic, Scottsdale, AZ.
  • de Alarcon A; Department of Otolaryngology-Head and Neck Surgery, Mayo Clinic, Phoenix, AZ.
  • Orlikoff RF; Division of Pediatric Otolaryngology, Cincinnati Children's Hospital Medical Center, OH.
  • Naghibolhosseini M; Department of Otolaryngology-Head and Neck Surgery, University of Cincinnati, OH.
J Speech Lang Hear Res ; 65(6): 2098-2113, 2022 06 08.
Article in En | MEDLINE | ID: mdl-35605603
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Voice Disorders / Deep Learning / Larynx Type of study: Diagnostic_studies Limits: Humans Language: En Journal: J Speech Lang Hear Res Journal subject: AUDIOLOGIA / PATOLOGIA DA FALA E LINGUAGEM Year: 2022 Document type: Article Country of publication:
Fulltext
Add to My VHL
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Voice Disorders / Deep Learning / Larynx Type of study: Diagnostic_studies Limits: Humans Language: En Journal: J Speech Lang Hear Res Journal subject: AUDIOLOGIA / PATOLOGIA DA FALA E LINGUAGEM Year: 2022 Document type: Article Country of publication: