Real-Time Estimation of Tibialis Anterior Muscle Thickness from Dysfunctional Lower Limbs Using Sonography

Muscle thickness is an important parameter related to musculoskeletal functions and has been studied in many ways and for various purposes. In recent years, ultrasound imaging has been widely used for measuring muscle properties of human muscles non-invasively, with the advantages of real time and low cost. The muscle thickness is usually measured manually, which is subjective and time consuming. In addition, there are few studies on automatic estimation of muscle thickness during dynamic contraction. In this study, an automatic estimation method based on compressive tracking algorithm is proposed to detect the thickness changes of tibialis anterior muscle during dynamic contraction on ultrasound images. The performance of the proposed method is compared to manual detection using clinical images from tibialis anterior muscles of ten patients. As a result, we found that the proposed method agrees well with the manual measurement, and it was able to provide an accurate and efficient approach for estimating muscle thickness during human motion.