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Tracing vocal fold vibrations using level set segmentation method.

Tailong Shi1, Hyun June Kim1, Thomas Murry2

  • 1Department of Bioengineering, Santa Clara University, Santa Clara, CA, USA.

International Journal for Numerical Methods in Biomedical Engineering
|March 17, 2015
PubMed
Summary
This summary is machine-generated.

This study presents a novel method for automatically tracing vocal fold motion using high-speed digital imaging and a combination of level set methods and motion cues. This technique enhances the understanding of phonation and aids in diagnosing voice disorders.

Keywords:
high-speed laryngeal imaginglevel set image segmentationregion of interestvideokymogramvocal fold motion

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Area of Science:

  • Laryngology
  • Biomedical Engineering
  • Image Processing

Background:

  • High-speed digital imaging (HSDI) of the larynx offers insights into vocal fold kinematics.
  • Understanding phonation mechanisms and assessing voice disorders benefit from kinematic analysis.
  • Automatic vocal fold vibration tracing is crucial for correlating vibration patterns with voice quality.

Purpose of the Study:

  • To introduce a new image segmentation and automatic vocal fold motion tracing approach.
  • To combine the level set method with motion cues for enhanced analysis.
  • To apply this method to videokymogram (VKG)-form images derived from HSDI sequences.

Main Methods:

  • Developed a novel approach integrating level set methods and motion cues for vocal fold motion tracing.
  • Constructed a standard deviation (STD) image from HSDI sequences to map vocal fold motion extent.
  • Identified the glottal region of interest (ROI) using thresholding on the STD image.

Main Results:

  • The proposed method effectively segments and traces vocal fold motion in VKG-form images.
  • The STD image successfully highlights the extent of vocal fold vibration.
  • The approach was validated using clinical datasets of normal and pathological voice conditions.

Conclusions:

  • The combined level set and motion cue approach provides an effective tool for automatic vocal fold motion analysis.
  • This method aids in the kinematic analysis of phonation and the clinical assessment of voice disorders.
  • The technique shows promise for characterizing vocal fold vibrations in various voice conditions.