一种基于GAOF的早期面瘫运动估计方法

面部表情运动估计是面瘫早期诊断和治疗评价等领域即将出现的一种重要的关键技术。本文提出了一种基于遗传算法的光流方法 (OpticalFlowMethodbasedonGeneticAlgorithm ,GAOF)进行早期面瘫运动估计。该方法从面部动态图像序列中估计面部微小运动矢量分布、特征参量及动态模式 ,用于早期面瘫的定位诊断与治疗定量评价。对一组正常被试者与一组面部神经肌肉运动异常病人进行实验 ,结果表明 :该方法与其他诊断方法相结合 ,对于早期面瘫定位诊断和恢复程度定量评价非常有效。与其他方法相比具有定位客观 ,定量检测精度高和便于进行动态模式评价等优点

A MOTION ESTIMATION METHOD FOR INCIPIENT FACIAL PARALYSIS BASED ON GAOF

The motion estimation of facial paralysis is a key technique for the diagnosis and evaluation of incipient facial paralysis. In this paper, a novel method is developed to implement the motion estimation of incipient facial paralysis based on GAOF (Optical Flow Method based on Genetic Algorithm). Using this method, the motion vector distribution, features and dynamic pattern were assessed from the dynamic facial image sequences, allowing diagnosis of the site of incipient facial paralysis and assess progression or recovery profiles of patients. Experimental results of some normal and abnormal subjects are reported verifying that this method is effective in the determination of the sites of incipient facial paralysis and quantitative evaluation of recovery process. Compared with other methods, this approach has more advantages such as objectivity, accuracy and convenience for dynamic patterns.