Muscle thickness is one of the most widely used parameters for quantifying muscle function in both diagnosis and rehabilitation assessment. Ultrasound imaging has been frequently used to non-invasively study the thickness of human muscles as a reliable method. However, the measurement is traditionally conducted by manual digitization of reference points at the superior and inferior muscle fascias, thus it is subjective and time-consuming. In this paper, a novel method is proposed to detect the muscle thickness automatically. The superficial and deep fascias of a muscle are detected by line detection algorithm at the first ultrasound frame, and the image regions of interest (ROI) for the fascias are subsequently located and tracked by optical flow technique. The muscle thickness is geometrically obtained based on the location of the fascias for each frame. Six ultrasound sequences (250 frames in each sequence) are used to evaluate this method. The correlation coefficient of the detection results between the proposed method and manual method is 0.95±0.01, and the difference is −0.05±0.22mm. The linear regression of the total 1500 detections show that a good linear correlation between the results of the two methods is obtained (R 2 =0.981). The automated method proposed here provides an accurate, high repeatable and efficient approach for estimating fascicle thickness during human motion, thus justifying its application in biological sciences. 
Continuous thickness measurement of rectus femoris muscle in ultrasound image sequences: A completely automated approach