Glottal Gap tracking by a continuous background modeling using inpainting.
The visual examination of the vibration patterns of the vocal folds is an essential method to understand the phonation process and diagnose voice disorders. However, a detailed analysis of the phonation based on this technique requires a manual or a semi-automatic segmentation of the glottal area, w...
| Published in: | Medical & Biological Engineering & Computing Vol. 55; no. 12; pp. 2123 - 2142 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Published: |
Springer Nature
Dec2017
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=126132871&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 126132871 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Dec2017 vid: 55 iid: 12 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 126132871 126132871 144050689 NLM28550413 10.1007/s11517-017-1652-8 NLM28550413 126132871 ppf: 2123 ppct: 19 formats: fmt: @attributes: type: P tig: atl: Glottal Gap tracking by a continuous background modeling using inpainting. aug: au: Andrade-Miranda, Gustavo Godino-Llorente, Juan Godino-Llorente, Juan Ignacio affil: Center for Biomedical Technology , Universidad Politécnica de Madrid , Campus de Montegancedo, Crta. M40 km, 38 Madrid Spain sug: subj: Vocal Cords Physiology Phonation Physiology Image Processing, Computer Assisted Methods Middle Age Glottis Models, Biological Aged, 80 and Over Kinematics Videorecording Algorithms Male Adult Female Vibration Glottis Physiology Vocal Cords Scales Middle Aged: 45-64 years Aged, 80 & over Adult: 19-44 years Male Female ab: The visual examination of the vibration patterns of the vocal folds is an essential method to understand the phonation process and diagnose voice disorders. However, a detailed analysis of the phonation based on this technique requires a manual or a semi-automatic segmentation of the glottal area, which is difficult and time consuming. The present work presents a cuasi-automatic framework to accurately segment the glottal area introducing several techniques not explored before in the state of the art. The method takes advantage of the possibility of a minimal user intervention for those cases where the automatic computation fails. The presented method shows a reliable delimitation of the glottal gap, achieving an average improvement of 13 and 18% with respect to two other approaches found in the literature, while reducing the error of wrong detection of total closure instants. Additionally, the results suggest that the set of validation guidelines proposed can be used to standardize the criteria of accuracy and efficiency of the segmentation algorithms. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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