Videokymogram Analyzer Tool: Human-computer comparison

0561214 - ÚTIA 2023 RIV NL eng J - Článek v odborném periodiku
Zita, Aleš - Novozámský, Adam - Zitová, Barbara - Šorel, Michal - Herbst, Ch. - Vydrová, J. - Švec, J. G.
Videokymogram Analyzer Tool: Human-computer comparison.
Biomedical Signal Processing and Control. Roč. 78, č. 1 (2022), č. článku 103878. ISSN 1746-8094. E-ISSN 1746-8108
Grant CEP: GA TA ČR(CZ) TA04010877; GA TA ČR(CZ) TH04010422; GA ČR GA21-03921S
Institucionální podpora: RVO:67985556
Klíčová slova: Image analysis * Videokymography * Vocal fold vibrations
Obor OECD: Computer hardware and architecture
Impakt faktor: 5.1, rok: 2022
Způsob publikování: Omezený přístup
http://library.utia.cas.cz/separaty/2022/ZOI/zita-0561214.pdf https://www.sciencedirect.com/science/article/pii/S1746809422003883?via%3Dihub

Videokymography (VKG) is a modern video recording technique used in laryngology and phoniatrics to examine vocal fold vibrations. To obtain quantitative information on the vocal fold vibration, VKG image analysis is needed but no software has yet been validated for this purpose. Here, we introduce a validated software tool that aids clinicians to evaluate diagnostically important vibration characteristics in VKG and other types of kymographic recordings. State-of-the-art methods for automated image evaluation were implemented and tested on a set of videokymograms with a wide range of vibratory characteristics, including healthy and pathologic voices. The automated image segmentation results were compared to manual segmentation results of six evaluators revealing average differences smaller than one pixel. Furthermore, the automatically categorized vibratory parameters precisely agreed with the average visual assessment in 84 and 91 percent of the cases for pathological and healthy patients, respectively. Based on these results, the newly developed software was found to be a valid, reliable automated tool for the quantification of vocal fold vibrations from VKG images, offering a number of novel features relevant for clinical practice.
Trvalý link: https://hdl.handle.net/11104/0333902