Chen Yuanyuan, Maksym Geoffrey, Brown Timothy, Deng Linhong
Key Laboratory of Biorheological Science and Technology, Ministry of Education, Collge of Biongineering, Chongqing University, Chongqing 400044, People's Republic of China.
Chin J Physiol. 2013 Feb 28;56(1):52-7. doi: 10.4077/CJP.2013.BAA072.
Understanding the opening fluctuation of glottis is meaningful in diagnosing vocal cord dysfunction. Nasopharyngoscopy can offer a direct method for visualizing the opening and closing of the glottis. However, the large amount of image data presents a significant challenge for quantitative analysis of the video recordings. Thus, automatic image processing method allowing for batch analysis of glottic images becomes clinically important. Here, we present an image processing method using Gaussian smoothing filter and threshold segmentation, followed by differentiation and Canny image edge detection for tracking changes in glottis dimensions (the opening area). A quantitative assessment of true glottic size was also developed for calibration in our study. This method was used to analyze different video data acquired from clinical nasopharyngoscopy of 8 healthy subjects during either normal breathing, breathing with cough or with 'Hee' sound. The results indicated that the computed glottic area change waveform was consistent with the observed glottic fluctuation in the video from nasopharyngoscopy. Thus, our proposed method may provide an accurate and efficient detection of glottic aperture and quick assessment of glottic fluctuations to assist clinical diagnosis of vocal cord dysfunction and other airway pathologies.
了解声门的开口波动对于诊断声带功能障碍具有重要意义。鼻咽喉镜检查可以提供一种直接观察声门开闭的方法。然而，大量的图像数据给视频记录的定量分析带来了重大挑战。因此，能够对声门图像进行批量分析的自动图像处理方法在临床上变得至关重要。在此，我们提出一种图像处理方法，该方法使用高斯平滑滤波器和阈值分割，随后进行微分和Canny图像边缘检测以跟踪声门尺寸（开口面积）的变化。在我们的研究中，还开发了一种对真实声门大小进行定量评估的方法用于校准。该方法用于分析从8名健康受试者临床鼻咽喉镜检查中获取的不同视频数据，这些数据分别来自正常呼吸、咳嗽呼吸或发“Hee”音时的情况。结果表明，计算得到的声门面积变化波形与鼻咽喉镜视频中观察到的声门波动一致。因此，我们提出的方法可能提供一种准确且高效的声门孔径检测方法，并能快速评估声门波动，以辅助声带功能障碍和其他气道疾病的临床诊断。
