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Related Experiment Video

Updated: Jun 6, 2026

Three-dimensional Quantification of Intestinal Mucus Using Whole-mount Tissue Imaging

Three-dimensional Quantification of Intestinal Mucus Using Whole-mount Tissue Imaging

Published on: September 12, 2025

Objective detection and quantification of mucosal wave propagation.

Daniel Voigt¹, Michael Döllinger, Ulrich Eysholdt

¹Department of Phoniatrics and Pediatric Audiology, University Hospital Erlangen, Bohlenplatz 21, D-91054 Erlangen, Germany. daniel.voigt@uk-erlangen.de

The Journal of the Acoustical Society of America

|November 30, 2010

Summary

This study introduces a novel algorithm to detect mucosal wave propagation in vocal folds. The method quantitatively captures wave movement, enabling analysis of vocal fold activity for improved diagnostics.

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Area of Science:

Laryngology and Speech Science
Biomedical Engineering
Vocal Fold Dynamics

Background:

Understanding mucosal wave propagation is crucial for diagnosing vocal fold pathologies.
Current methods for analyzing vocal fold dynamics may lack quantitative precision.
Objective assessment of vocal fold vibration is essential for clinical applications.

Purpose of the Study:

To present a new detection algorithm for quantifying mucosal wave propagation.
To analyze the spatio-temporal characteristics of mucosal waves.
To differentiate types of mucosal wave activity based on velocity and symmetry.

Main Methods:

Development of a detection algorithm based on vocal fold edge movement.
Incorporation of physiological knowledge of mucosal wave properties.
Quantitative capture of the spatio-temporal position of the mucosal wave.
Analysis of laryngeal high-speed recordings.

Main Results:

Successful detection and analysis of mucosal wave propagation.
Quantitative capture of spatio-temporal wave positions.
Discrimination of different mucosal wave activities (spread velocity, symmetry).
Promising preliminary results from six laryngeal recordings.

Conclusions:

The proposed algorithm enables objective detection and description of mucosal wave propagation.
This approach shows potential for enhanced diagnosis of vocal fold conditions.
Further validation on larger datasets is warranted.