Ultrasound imaging and semi-automatic analysis of active muscle features in electrical stimulation by optical flow

Ultrasound imaging is an effective way to measure the muscle activity in electrical stimulation studies. However, it is a time consuming task to manually measure pennation angle and muscle thickness, which are the benchmark features to analyze muscle activity from the ultrasound imaging. In previous studies, the muscle features were measured by calculating optical flow of the pennation angle by using only fibers of a muscle from the ultrasound, without carefully considering moving muscle edges during active and passive contraction. Therefore, this study aimed to measure the pennation angle and muscle thickness by using the edges and fibers of a muscle in a quantitative way in a semi-automatic optical flow based approach. The results of the semi-automatic analysis were compared to that of manual measurement. Through the comparison, it is clear that the proposed algorithm could achieve higher accuracy in tracking the thickness and pennation angle for a sequence of ultrasound images.