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使用Kinect v2对面瘫进行量化。

Quantifying facial paralysis using the Kinect v2.

作者信息

Gaber Amira, Taher Mona F, Wahed Manal Abdel

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2015;2015:2497-501. doi: 10.1109/EMBC.2015.7318899.

Abstract

Assessment of facial paralysis (FP) and quantitative grading of facial asymmetry are essential in order to quantify the extent of the condition as well as to follow its improvement or progression. As such, there is a need for an accurate quantitative grading system that is easy to use, inexpensive and has minimal inter-observer variability. A comprehensive automated system to quantify and grade FP is the main objective of this work. An initial prototype has been presented by the authors. The present research aims to enhance the accuracy and robustness of one of this system's modules: the resting symmetry module. This is achieved by including several modifications to the computation method of the symmetry index (SI) for the eyebrows, eyes and mouth. These modifications are the gamma correction technique, the area of the eyes, and the slope of the mouth. The system was tested on normal subjects and showed promising results. The mean SI of the eyebrows decreased slightly from 98.42% to 98.04% using the modified method while the mean SI for the eyes and mouth increased from 96.93% to 99.63% and from 95.6% to 98.11% respectively while using the modified method. The system is easy to use, inexpensive, automated and fast, has no inter-observer variability and is thus well suited for clinical use.

摘要

对面部麻痹(FP)进行评估以及对面部不对称进行定量分级,对于量化病情严重程度以及跟踪其改善或进展情况至关重要。因此,需要一种准确、易于使用、成本低廉且观察者间差异最小的定量分级系统。开发一个全面的自动化系统来对面部麻痹进行量化和分级是这项工作的主要目标。作者已经展示了一个初始原型。本研究旨在提高该系统其中一个模块——静息对称模块的准确性和稳健性。这通过对眉毛、眼睛和嘴巴的对称指数(SI)计算方法进行若干修改来实现。这些修改包括伽马校正技术、眼睛区域以及嘴巴斜率。该系统在正常受试者身上进行了测试,并显示出了有前景的结果。使用改进方法时,眉毛的平均对称指数从98.42%略微降至98.04%,而眼睛和嘴巴的平均对称指数分别从96.93%增至99.63%以及从95.6%增至98.11%。该系统易于使用、成本低廉、自动化且速度快,不存在观察者间差异,因此非常适合临床使用

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