• Title of article

    Vocal Folds Analysis Using Global Energy Tracking

  • Author/Authors

    Gal Elidan، نويسنده , , Josef Elidan، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2012
  • Pages
    9
  • From page
    760
  • To page
    768
  • Abstract
    Introduction Detection and quantification of oscillatory irregularities in laryngeal videostroboscopy can be particularly difficult for the human expert. Accordingly, there is a wide interest in automated methods for recovering the foldsʹ temporal trajectory. Unfortunately, current methods typically provide only crude glottal measurements. Objectives An automated procedure for consistently tracking the entire vocal foldsʹ boundary in laryngeal stroboscopy videos, even when the glottal opening is closed. Methods A preprocessing frame-by-frame crude midpoint identification is followed by an active contour evolution to detect the global boundary in each frame independently. A global energy active contour is then jointly defined over the entire video sequence, and the full glottal boundary is detected throughout the video via standard energy minimization. Results The vocal foldsʹ boundary is accurately tracked in normal and abnormal stroboscopy videos collected inآ a clinical setting, and that exhibit a varied range of visual characteristics (eg, lighting conditions). A proof-of-concept evaluation based on the analysis of the waveform of the location of points along the boundary separates between a normal andآ two markedly different abnormal subjects, and automatically provides a hypothesized localization of the abnormality. Conclusion The first method for automatically tracing the temporal trajectory of all points along the vocal foldsʹ boundary in all frames of a stroboscopy video is presented. The approach opens the door for novel analysis of all regions of the contour, which in turn may lead to automated localization of pathologies.
  • Keywords
    Vocal fold analysis , Automated tracking , active contours , Stroboscopy video
  • Journal title
    Journal of Voice
  • Serial Year
    2012
  • Journal title
    Journal of Voice
  • Record number

    1280937