Département de radiologie, Centre hospitalier de l'Université de Montréal, Québec, Canada.
J Neurosci Methods. 2010 Jul 15;190(2):279-88. doi: 10.1016/j.jneumeth.2010.05.006. Epub 2010 May 21.
A computer-aided method for the tracking of morphological markers in fluoroscopic images of a rat walking on a treadmill is presented and validated. The markers correspond to bone articulations in a hind leg and are used to define the hip, knee, ankle and metatarsophalangeal joints. The method allows a user to identify, using a computer mouse, about 20% of the marker positions in a video and interpolate their trajectories from frame-to-frame. This results in a seven-fold speed improvement in detecting markers. This also eliminates confusion problems due to legs crossing and blurred images. The video images are corrected for geometric distortions from the X-ray camera, wavelet denoised, to preserve the sharpness of minute bone structures, and contrast enhanced. From those images, the marker positions across video frames are extracted, corrected for rat "solid body" motions on the treadmill, and used to compute the positional and angular gait patterns. Robust Bootstrap estimates of those gait patterns and their prediction and confidence bands are finally generated. The gait patterns are invaluable tools to study the locomotion of healthy animals or the complex process of locomotion recovery in animals with injuries. The method could, in principle, be adapted to analyze the locomotion of other animals as long as a fluoroscopic imager and a treadmill are available.
介绍并验证了一种用于在跑步机上行走的老鼠荧光透视图像中形态标记物跟踪的计算机辅助方法。这些标记物对应后腿中的骨关节,用于定义髋关节、膝关节、踝关节和跖趾关节。该方法允许用户使用计算机鼠标在视频中识别大约 20%的标记位置,并逐帧内插它们的轨迹。这使得检测标记的速度提高了七倍。这也消除了由于腿部交叉和图像模糊而导致的混淆问题。从 X 射线相机校正视频图像的几何失真,使用小波去噪来保持微小骨结构的清晰度,并增强对比度。从这些图像中提取视频帧之间的标记位置,校正跑步机上老鼠“实体”运动的影响,并用于计算位置和角度步态模式。最后生成这些步态模式及其预测和置信带的稳健自举估计。步态模式是研究健康动物运动或受伤动物复杂运动恢复过程的宝贵工具。只要有荧光透视成像仪和跑步机,该方法原则上可以适应分析其他动物的运动。