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Regional Assessment of Facial Nerve Paralysis Using Optical Flow Method

机译:采用光学流动法对面神经瘫痪的区域评估

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The face composed of variation of facial muscles which are responsible to interact through the expressions. The facial nerve contains approximately 10,000 of fibers and any damage to these facial nerve will affects all of muscles associated with facial expressions. Thus, it is one of the most extensive destruction in peripheral nerve injuries which demanded for rapid and accurate commencement of assessment to a better treatment and rehabilitation. The traditional methods involved the subjective assessment of medical professionals which may lead to observer error and acquired different decisions on treatment method. However, an ideal and good objective assessment system is still have to rely on a standardized scale to make it more fits to clinicians' use for daily applications. In this study, a diagnosis system for the quantitative assessment of facial nerve paralysis has been proposed using optical flow method which provides the degree of precise movements based on House-Brackmann system on each regional parts of face. The system is not only provided the right-left ratio of facial movement to present the side of paralysis, but also offered the regional score for each movements which lead to total score and afforded the most important highlighted scores, which is the House-Brackmann score for each subjects. The regional scores by using the distance measurement has shown the most outstanding result, at about 98% in classifying the patients and may become a great aid to clinicians in determining the condition of patients from the offset of the paralysis.
机译:由面部肌肉的变异组成的面部,这些肌肉是负责通过表情互动的。面神经含有大约10,000个纤维,并且对这些面神经的任何损伤会影响与面部表情相关的所有肌肉。因此,它是周围神经伤害最广泛的破坏之一,要求快速准确地开始评估,以更好的治疗和康复。传统方法涉及医疗专业人员的主观评估,这可能导致观察者误差并获得对治疗方法的不同决策。然而,理想和良好的客观评估系统仍然必须依赖标准化规模来使其更适合临床医生对日常应用的使用。在本研究中,使用光学流动方法提出了一种用于定量评估面神经瘫痪的诊断系统,该光学流量方法提供了基于脸部各个区域部位的房屋 - Brackmann系统的精确运动程度。该系统不仅提供了面部运动的右左偏差,而且还提供了每个运动的区域分数,这导致总分,并提供了最重要的突出显示的分数,这是房屋 - Brackmann得分对于每个科目。通过使用距离测量的区域分数显示出最优秀的结果,在分类患者时大约98%,可能成为临床医生的巨大援助,以确定瘫痪患者的状况。

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