Automatic Tracing of Vocal Fold Motion in High Speed Laryngeal Video Erik Bieging

Vocal Fold Imaging  Human vocal folds oscillate at 100 to 400 Hz during normal phonation  High-speed digital imaging (4000 frames/sec) is used to study the motion of the vocal folds  Automated methods are needed to extract edge of glottis and glottal area Vocal Folds Glottis

Current Methods Histogram method  Threshold is applied to separate glottis and vocal fold tissue  Threshold is determined from each frame’s histogram Thresh

Current Methods Region Growing  Seeds are started at darkest points in image  Regions are grown based on similarity between region pixels and surrounding pixels Active Contour  Initial region is defined using thresholding  Edge is iteratively moved based on image gradient and several parameters

New Differentiation Based Method  Each column of the image is passed through a smoothing differentiating filter  Max and min of derivative are taken to be glottal edges  Binary image created  Canny edge detection applied to binary image to smooth the edge

Comparison of Methods (a) (b) (c) (d) (e) High Quality Data: Lower Quality Data: (a)Original Image (b)Histogram (c)Region Growing (d)Active Contour (e)New Method

Comparison of Methods

Results  100 frames from 10 videos were analyzed with each method  Deviation from manually detected glottal area calculated VideoHistogram Region Growin g Active Cont ourOur Method %197.55%62.98%15.53% %26.58%38.73%5.71% 33.93%5.50%40.38%1.85% %16.31%44.95%4.02% %21.58%43.85%18.72% %7.31%57.54%14.02% %18.21%34.11%3.05% 86.23%4.42%41.13%4.75% %47.29%38.92%12.97% %10.73%39.77%10.60% Average31.49%35.55%44.24%9.12%

Computaion Time  Average time to analyze 100 frames:  Histogram: 2.09 min.  Region Growing: min.  Active Contour: min.  New method: 1.21 min