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13 March 2013 Glottis segmentation using dynamic programming
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Proceedings Volume 8669, Medical Imaging 2013: Image Processing; 86693L (2013)
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States
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.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jing Chen, Bahadir K. Gunturk, and Melda Kunduk "Glottis segmentation using dynamic programming", Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 86693L (13 March 2013);


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