A Deep Learning Enhanced Novel Software Tool for Laryngeal Dynamics Analysis.
Purpose: High-speed videoendoscopy (HSV) is an emerging, but barely used, endoscopy technique in the clinic to assess and diagnose voice disorders because of the lack of dedicated software to analyze the data. HSV allows to quantify the vocal fold oscillations by segmenting the glottal area. This ch...
| Published in: | Journal of Speech, Language & Hearing Research Vol. 64; no. 6; pp. 1889 - 1904 |
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| Main Authors: | , , , , , , , , , , |
| Format: | Article |
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American Speech-Language-Hearing Association
Jun2021
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=150778854&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 150778854 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 10924388 1SM jtl: Journal of Speech, Language & Hearing Research issn: 10924388 maglogo: N pubinfo: dt: Jun2021 vid: 64 iid: 6 pid: 42 pub: American Speech-Language-Hearing Association artinfo: ui: 150778854 10.1044/2021_JSLHR-20-00498 ppf: 1889 ppct: 15 formats: fmt: @attributes: type: P size: 1.3MB tig: atl: A Deep Learning Enhanced Novel Software Tool for Laryngeal Dynamics Analysis. aug: au: Kist, Andreas M. Gómez, Pablo Dubrovskiy, Denis Schlegel, Patrick Kunduk, Melda Echternach, Matthias Patel, Rita Semmler, Marion Stephan Dürr, Christopher Bohr,e Schützenberger, Anne Döllinger, Michael affil: Division of Phoniatrics and Pediatric Audiology, Department of Otorhinolaryngology—Head & Neck Surgery, University Hospital Erlangen, Germany. Department of Communication Sciences and Disorders, Louisiana State University, Baton Rouge. Division of Phoniatrics and Pediatric Audiology, Department of Otorhinolaryngology, Munich University Hospital (LMU), Germany. Department of Speech, Language and Hearing Sciences, College of Arts and Sciences, Indiana University, Bloomington. su: Deep learning Computer software Glottis Artificial neural networks Video recording Graphical user interfaces Algorithms sug: subj: Computer, computer peripheral and pre-packaged software merchant wholesalers Computer and Computer Peripheral Equipment and Software Merchant Wholesalers Computer and software stores Software publishers (except video game publishers) Deep learning Computer software Glottis Artificial neural networks Video recording Graphical user interfaces Algorithms ab: Purpose: High-speed videoendoscopy (HSV) is an emerging, but barely used, endoscopy technique in the clinic to assess and diagnose voice disorders because of the lack of dedicated software to analyze the data. HSV allows to quantify the vocal fold oscillations by segmenting the glottal area. This challenging task has been tackled by various studies; however, the proposed approaches are mostly limited and not suitable for daily clinical routine. Method: We developed a user-friendly software in C# that allows the editing, motion correction, segmentation, and quantitative analysis of HSV data. We further provide pretrained deep neural networks for fully automatic glottis segmentation. Results: We freely provide our software Glottis Analysis Tools (GAT). Using GAT, we provide a general thresholdbased region growing platform that enables the user to analyze data from various sources, such as in vivo recordings, ex vivo recordings, and high-speed footage of artificial vocal folds. Additionally, especially for in vivo recordings, we provide three robust neural networks at various speed and quality settings to allow a fully automatic glottis segmentation needed for application by untrained personnel. GAT further evaluates video and audio data in parallel and is able to extract various features from the video data, among others the glottal area waveform, that is, the changing glottal area over time. In total, GAT provides 79 unique quantitative analysis parameters for video- and audio-based signals. Many of these parameters have already been shown to reflect voice disorders, highlighting the clinical importance and usefulness of the GAT software. Conclusion: GAT is a unique tool to process HSV and audio data to determine quantitative, clinically relevant parameters for research, diagnosis, and treatment of laryngeal disorders. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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