Visual and Automatic Evaluation of Vocal Fold Mucosal Waves Through Sharpness of Lateral Peaks in High-Speed Videokymographic Images.

INTRODUCTION: The sharpness of lateral peaks is a visually helpful clinical feature in high-speed videokymographic (VKG) images indicating vertical phase differences and mucosal waves on the vibrating vocal folds and giving insights into the health and pliability of vocal fold mucosa. This study aims at investigating parameters that can be helpful in objectively quantifying the lateral peak sharpness from the VKG images. METHOD: Forty-five clinical VKG images with different degrees of sharpness of lateral peaks were independently evaluated visually by three raters. The ratings were compared to parameters obtained by automatic image analysis of the vocal fold contours: Open Time Percentage Quotients (OTQ) and Plateau Quotients (PQ). The OTQ parameters were derived as fractions of the period during which the vocal fold displacement exceeds a predetermined percentage of the vibratory amplitude. The PQ parameters were derived similarly but as a fraction of the open phase instead of a period. RESULTS: The best correspondence between the visual ratings and the automatically derived quotients were found for the OTQ and PQ parameters derived at 95% and 80% of the amplitude, named OTQ95, PQ95, OTQ80 and PQ80. Their Spearman's rank correlation coefficients were in the range of 0.73 to 0.77 (P < 0.001) indicating strong relationships with the visual ratings. The strengths of these correlations were similar to those found from inter-rater comparisons of visual evaluations of peak sharpness. CONCLUSION: The Open time percentage and Plateau quotients at 95% and 80% of the amplitude stood out as the possible candidates for capturing the sharpness of the lateral peaks with their reliability comparable to that of visual ratings.

PIZZARO: Forensic analysis and restoration of image and video data.

This paper introduces a set of methods for image and video forensic analysis. They were designed to help to assess image and video credibility and origin and to restore and increase image quality by diminishing unwanted blur, noise, and other possible artifacts. The motivation came from the best practices used in the criminal investigation utilizing images and/or videos. The determination of the image source, the verification of the image content, and image restoration were identified as the most important issues of which automation can facilitate criminalists work. Novel theoretical results complemented with existing approaches (LCD re-capture detection and denoising) were implemented in the PIZZARO software tool, which consists of the image processing functionality as well as of reporting and archiving functions to ensure the repeatability of image analysis procedures and thus fulfills formal aspects of the image/video analysis work. Comparison of new proposed methods with the state of the art approaches is shown. Real use cases are presented, which illustrate the functionality of the developed methods and demonstrate their applicability in different situations. The use cases as well as the method design were solved in tight cooperation of scientists from the Institute of Criminalistics, National Drug Headquarters of the Criminal Police and Investigation Service of the Police of the Czech Republic, and image processing experts from the Czech Academy of Sciences.