0396304 20240103202954.420130926235959.9 1 s. C cav_un_epca*03939661805-869811 (2013)49-49 videokymography image processing computerassisted evaluation cav_un_auth*0283562 Novozámský Adam Zpracování obrazové informace Department of Image Processing ZOI ZOI UTIA-B Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0239988 Sedlář Jiří Zpracování obrazové informace Department of Image Processing ZOI ZOI UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0294185 Zita A. CZ cav_un_auth*0018322 Švec J. G. CZ cav_un_auth*0101238 Zitová Barbara Zpracování obrazové informace Department of Image Processing ZOI ZOI UTIA-B Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101087 Flusser Jan Zpracování obrazové informace Department of Image Processing ZOI ZOI UTIA-B Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0277479 Hauzar D. CZ http://library.utia.cas.cz/separaty/2013/ZOI/novozamsky-computer-assisted evaluation of videokymographic data.pdf Videokymography is a novel medical imaging method used in laryngology and phoniatrics for observation and diagnosis of vocal fold vibrations. The amount and the quality of the data hamper manual feature extraction. A computer-assisted extraction could facilitate the diagnostic process. The proposed solution offers a software tool for data enhancement and extraction of typical characteristics of vocal folds vibrations designed by experts. The proposed methodology is based on digital image processing methods, namely image denoising, image segmentation, and object detection. Such approach enables to reflect specific features of videokymographic images and extracted vocal fold parameters. We have tested the proposed solutions on a representative set of videokymographic data. The comparison of the achieved results with the visually detected features proved the method applicability. The algorithms were implemented into the VKFD (videokymography feature detection) software. cav_un_auth*0293266 EFMI STC Prague Data and Knowledge for Medical Decision Support Praha 17.04.2013-19.04.2013 CZ 2014 JD 7 4 O 4o 20231122135811.5 PO RVO:67985556 http://hdl.handle.net/11104/0224132 2013 Soubory v repozitáři: 0396304.pdf cav_un_epca*0393966 International Journal on Biomedicine and Healthcare 1805-8698 Roč. 1 č. 1 2013 49 49