A Fast Semiautomatic Algorithm for Centerline-Based Vocal Tract Segmentation.

Vocal tract morphology is an important factor in voice production. Its analysis has potential implications for educational matters as well as medical issues like voice therapy.The knowledge of the complex adjustments in the spatial geometry of the vocal tract during phonation is still limited. For a...

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Published in:BioMed Research International Vol. 2015; pp. 1 - 8
Main Authors: Poznyakovskiy, Anton A., Mainka, Alexander, Platzek, Ivan, Mürbe, Dirk
Format: diagnostic images equations & formulas research tables/charts Journal Article
Published: Wiley-Blackwell 10/18/2015
Online Access:View this record in EBSCOhost
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      dt: 10/18/2015
      vid: 2015
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1155/2015/906356
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        atl: A Fast Semiautomatic Algorithm for Centerline-Based Vocal Tract Segmentation.
      aug:
        au:
          Poznyakovskiy, Anton A.
          Mainka, Alexander
          Platzek, Ivan
          Mürbe, Dirk
        affil: Department of Otorhinolaryngology, University Hospital Carl Gustav Carus, Technische Universität Dresden, 01062 Dresden, Germany
      sug:
        subj:
          Algorithms
          Vocal Cords
          Magnetic Resonance Imaging
          Phonation
          Vowels
          Automation
          Imaging, Three-Dimensional
          Human
          Models, Structural
          Speech
          Singing
      ab: Vocal tract morphology is an important factor in voice production. Its analysis has potential implications for educational matters as well as medical issues like voice therapy.The knowledge of the complex adjustments in the spatial geometry of the vocal tract during phonation is still limited. For a major part, this is due to difficulties in acquiring geometry data of the vocal tract in the process of voice production. In this study, a centerline-based segmentationmethod using active contours was introduced to extract the geometry data of the vocal tract obtained with MRI during sustained vowel phonation. The applied semiautomatic algorithm was found to be time- and interaction-efficient and allowed performing various three-dimensional measurements on the resulting model. The method is suitable for an improved detailed analysis of the vocal tract morphology during speech or singing which might give some insights into the underlying mechanical processes.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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