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Development of a computerized system for analyzing facial nerve paralysis -A method using the optical flow-

面神经麻痹分析计算机系统的开发-使用光流的方法-

基本信息

批准号：
12671681
负责人：
KUNIHIRO Takanobu
金额：
$ 2.43万
依托单位：
Keio University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2000
资助国家：
日本
起止时间：
2000 至 2001
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-12671681/
关键词：
facial nerve palsy objective assessment optical flow computer gradient method 評価法

项目摘要

We developed a computerized system to assess the degree of facial nerve paralysis. Our system calculates the optical flow throughout the facial area, using the gradient method.The results obtained with our system were both precise and reproducible. They were almost identical to those obtained using the matching method, and the inter-examiner variability was minimal. In addition, when expressed using the diseased-to-healthy side ratio of the optical flow, the results correlated well with the scores assigned to each facial movement using Yanagihara's grading scale. The optical flow index, which we defined using the results, is also highly correlated with the total scores on Yanagihara's grading scale.Another advantage of our system is that it permits flexible expression of the analysis results. For example, the optical flow for each small area within the facial region can be superimposed on the original picture of the patient. This enables intuitive understanding of the facial movements. Furthermore, the movement of each pixel in the facial region can be traced on a frame-to-frame basis. These two features are very useful for assessing associated movements.Our system initially ran only on Linux, but it now also works on Windows. We expect that our system will be used widely in daily clinical practice.

我们开发了一个计算机系统来评估面部神经麻痹的程度。我们的系统使用梯度法计算整个面部区域的光流。用我们的系统获得的结果既精确又可重复。它们与使用匹配方法获得的结果几乎相同，检查者间的变异性极小。此外，当使用光流的患病侧与健康侧的比率表示时，结果与使用Yanagihara分级量表分配给每个面部运动的分数相关性良好。根据该结果定义的光流指数与柳原评分量表的总分也高度相关。该系统的另一个优点是可以灵活地表达分析结果。例如，可以将面部区域内的每个小区域的光流叠加在患者的原始图片上。这使得能够直观地理解面部运动。此外，可以逐帧地跟踪面部区域中的每个像素的移动。这两个功能对于评估相关运动非常有用。我们的系统最初只在Linux上运行，但现在也可以在Windows上运行。我们希望我们的系统将在日常临床实践中广泛使用。