Kuo Chung-Feng Jeffrey, Kuo Joseph, Hsiao Shang-Wun, Lee Chi-Lung, Lee Jih-Chin, Ke Bo-Han
1 Department of Materials Science and Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan.
2 Wisconsin State Laboratory of Hygiene, Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI, USA.
Proc Inst Mech Eng H. 2017 Jan;231(1):48-57. doi: 10.1177/0954411916679200. Epub 2016 Dec 21.
The laryngeal video stroboscope is an important instrument for physicians to analyze abnormalities and diseases in the glottal area. Stroboscope has been widely used around the world. However, without quantized indices, physicians can only make subjective judgment on glottal images. We designed a new laser projection marking module and applied it onto the laryngeal video stroboscope to provide scale conversion reference parameters for glottal imaging and to convert the physiological parameters of glottis. Image processing technology was used to segment the important image regions of interest. Information of the glottis was quantified, and the vocal fold image segmentation system was completed to assist clinical diagnosis and increase accuracy. Regarding image processing, histogram equalization was used to enhance glottis image contrast. The center weighted median filters image noise while retaining the texture of the glottal image. Statistical threshold determination was used for automatic segmentation of a glottal image. As the glottis image contains saliva and light spots, which are classified as the noise of the image, noise was eliminated by erosion, expansion, disconnection, and closure techniques to highlight the vocal area. We also used image processing to automatically identify an image of vocal fold region in order to quantify information from the glottal image, such as glottal area, vocal fold perimeter, vocal fold length, glottal width, and vocal fold angle. The quantized glottis image database was created to assist physicians in diagnosing glottis diseases more objectively.
喉动态电子喉镜是医生分析声门区异常和疾病的重要仪器。动态喉镜已在全球广泛使用。然而，由于缺乏量化指标，医生只能对声门图像进行主观判断。我们设计了一种新的激光投影标记模块，并将其应用于喉动态电子喉镜，为声门成像提供比例转换参考参数，并转换声门的生理参数。利用图像处理技术分割重要的感兴趣图像区域。对声门信息进行量化，完成声带图像分割系统，以辅助临床诊断并提高准确性。在图像处理方面，使用直方图均衡化来增强声门图像的对比度。中心加权中值滤波器在保留声门图像纹理的同时滤除图像噪声。采用统计阈值确定法对声门图像进行自动分割。由于声门图像包含唾液和光斑，这些被归类为图像噪声，通过腐蚀、膨胀、断开和闭合技术消除噪声，以突出声带区域。我们还利用图像处理自动识别声带区域的图像，以便量化声门图像中的信息，如声门面积、声带周长、声带长度、声门宽度和声带角度。创建了量化的声门图像数据库，以帮助医生更客观地诊断声门疾病。
