  We compare four different algorithms for automatically estimating the muscle
fascicle angle from ultrasonic images: the vesselness filter, the Radon
transform, the projection profile method and the gray level cooccurence matrix
(GLCM). The algorithm results are compared to ground truth data generated by
three different experts on 425 image frames from two videos recorded during
different types of motion. The best agreement with the ground truth data was
achieved by a combination of pre-processing with a vesselness filter and
measuring the angle with the projection profile method. The robustness of the
estimation is increased by applying the algorithms to subregions with high
gradients and performing a LOESS fit through these estimates.
