Computer Engineering Department, Faculty of Electrical & Electronics Engineering, Yildiz Technical University, 34220, Istanbul, Turkey.
Med Biol Eng Comput. 2019 Nov;57(11):2535-2552. doi: 10.1007/s11517-019-02031-9. Epub 2019 Sep 6.
Clinical diagnosis of voice pathologies is performed by analyzing audio, color, shape, and vibration patterns of the laryngeal recordings which are taken with medical imaging devices such as video-laryngostroboscope, direct laryngoscopy, and high-speed videoendoscopes. This paper examines state-of-the-art methods and reveals open issues and problems of computing solutions for analysis and identification of laryngeal disorders. We propose a categorical representation of the most significant applications published so far in terms of their scopes, used methodologies, and achieved results. Laryngeal image/video analysis is discussed in four main categories: segmentation of vocal folds, classification of vocal fold disorders, vocal fold vibration analysis, and vocal fold image stitching. By this study, we reveal new opportunities and potentials of vision-based computerized solutions for evaluation, early diagnosis, and prevention of laryngeal disorders. Graphical abstract.
临床嗓音病理学的诊断是通过分析喉部记录的音频、颜色、形状和振动模式来进行的，这些记录是使用视频喉镜、直接喉镜和高速视频内窥镜等医学成像设备获取的。本文研究了最新的方法，并揭示了计算分析和识别喉部疾病的解决方案中存在的问题和开放性问题。我们根据其范围、使用的方法和取得的结果，对迄今为止发表的最重要的应用进行了分类表示。本文从四个主要类别讨论了喉图像/视频分析：声带分割、声带疾病分类、声带振动分析和声带图像拼接。通过这项研究，我们揭示了基于视觉的计算机化解决方案在评估、早期诊断和预防喉部疾病方面的新机会和潜力。
