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Proceedings Paper

Motion analysis of videostroboscopic images of the larynx
Author(s): Abdul K. Saadah; Nikolas P. Galatsanos; D. Bless
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Paper Abstract

Videostroboscopy is an examination method during which a video-recording of the moving vocal folds is obtained. This examination, is very important because it yields a permanent record of the moving vocal folds and it allows the diagnosis of abnormalities which contribute to voice disorders. In this paper we use image processing algorithms in order to find and quantify the motion of the vocal folds during phonation. In order to achieve this, a new approach for tracking of the vocal folds is presented. More specifically, an active contours (snakes) based procedure is developed to automatically, with minimum user intervention, delineate the contour of the vocal folds in each frame of the videostroboscopic image sequence. After this delineation, an elastic registration algorithm is used to find the motion of the vocal folds between adjacent frames of a video sequence. For this purpose, a new simulated annealing based algorithm is used to match elastically the vocal fold contours from frame-to-frame. After the motion of each point of the vocal folds has been estimated, an affine model is used to parameterize the motion from frame-to-frame. Least-squares estimation is used to fit this model. The parameters of such a model (rotation, translation, and deformation along two principle axes) will hopefully help quantify and discriminate videostroboscopic recordings based on the motion present.

Paper Details

Date Published: 8 April 1996
PDF: 12 pages
Proc. SPIE 2709, Medical Imaging 1996: Physiology and Function from Multidimensional Images, (8 April 1996); doi: 10.1117/12.237858
Show Author Affiliations
Abdul K. Saadah, Illinois Institute of Technology (United States)
Nikolas P. Galatsanos, Illinois Institute of Technology (United States)
D. Bless, Univ. of Wisconsin/Madison (United States)

Published in SPIE Proceedings Vol. 2709:
Medical Imaging 1996: Physiology and Function from Multidimensional Images
Eric A. Hoffman, Editor(s)

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