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Development and validation of ultrasound speckle tracking to quantify tendon displacement.

机译:超声散斑跟踪的发展和验证,以量化肌腱位移。

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摘要

Ultrasound can be used to study tendon movement. However, measurement of tendon movement is mostly based on manual tracking of anatomical landmarks such as the musculo-tendinous junction, limiting the applicability to a small number of muscle-tendon units. The aim of this study was to quantify tendon displacement without anatomical landmarks using a speckle tracking algorithm optimized for tendons in long B-mode image sequences. A dedicated two-dimensional multi-kernel block-matching scheme with subpixel motion estimation was devised to handle large displacements over long sequences. The accuracy of the tracking on porcine tendons was evaluated during different displacements and velocities. Subsequently, the accuracy of tracking the flexor digitorum superficialis (FDS) of a human cadaver hand was evaluated. Finally, the in-vivo accuracy of the tendon tracking was determined by measuring the movement of the FDS at the wrist level. For the porcine experiment and the human cadaver arm experiment tracking errors were, on average, 0.08 and 0.05mm, respectively (1.3% and 1.0%). For the in-vivo experiment the tracking error was, on average, 0.3mm (1.6%). This study demonstrated that our dedicated speckle tracking can quantify tendon displacement at different physiological velocities without anatomical landmarks with high accuracy. The technique allows tracking over large displacements and in a wider range of tendons than by using anatomical landmarks.
机译:超声可用于研究肌腱运动。但是,肌腱运动的测量主要基于对解剖标志物(例如肌肉与腱交界处)的手动跟踪,从而将其适用性限制于少量的肌腱单元。这项研究的目的是使用针对长B模式图像序列中的肌腱优化的斑点跟踪算法来量化没有解剖标志的肌腱移位。设计了带有子像素运动估计的专用二维多核块匹配方案,以处理长序列上的大位移。在不同的位移和速度下评估猪腱的追踪精度。随后,评估了跟踪人体尸体手的浅指屈肌(FDS)的准确性。最后,通过在腕部水平测量FDS的运动来确定肌腱追踪的体内准确性。对于猪实验和人体尸体实验,跟踪误差平均分别为0.08和0.05mm(1.3%和1.0%)。对于体内实验,跟踪误差平均为0.3毫米(1.6%)。这项研究表明,我们专用的散斑跟踪可以高精度地量化不同生理速度下的肌腱位移,而无解剖标志。与使用解剖标志相比,该技术可以跟踪较大的位移和较大范围的肌腱。

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