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Proceedings Paper

Glottis segmentation using dynamic programming
Author(s): Jing Chen; Bahadir K. Gunturk; Melda Kunduk
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Paper Abstract

High speed videoendoscopy (HSV) is widely used for the assessment of vocal fold vibratory behavior. Due to the huge volume of HSV data, an automated and accurate segmentation of glottal opening is demanded for objective quantification and analysis of vocal fold vibratory characteristics. In this study, a simplified dynamic programming based algorithm is presented to do glottis segmentation. The underlying idea is to track glottal edge in gradient image, where the average gradient magnitude along edge path is assumed to be maximal. To achieve accurate segmentation results and enable further analysis, we addressed different aspects of the problem, including reflection removal, detection of posterior and anterior commissures and determination of open and closed portions of glottal area. Reflection removal, which is essential for robust segmentation, is also achieved by dynamic programming. Posterior and anterior commissures in each frame of HSV data help pre-define the range of glottal area which needs to be segmented and therefore decrease the segmentation cost. In addition to the proposed algorithm, three other methods (including active contour, standard dynamic programming and fixed-threshold segmentation) have been implemented. The experimental results show that the proposed algorithm is more efficient and accurate than the others.

Paper Details

Date Published: 13 March 2013
PDF: 9 pages
Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 86693L (13 March 2013); doi: 10.1117/12.2006699
Show Author Affiliations
Jing Chen, Louisiana State Univ. (United States)
Bahadir K. Gunturk, Louisiana State Univ. (United States)
Melda Kunduk, Louisiana State Univ. (United States)


Published in SPIE Proceedings Vol. 8669:
Medical Imaging 2013: Image Processing
Sebastien Ourselin; David R. Haynor, Editor(s)

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