Estimating Skeletal Muscle Fascicle Curvature from B-Mode Ultrasound Image Sequences

摘要

We address the problem of tracking in vivo muscle fascicle shape and length changes using ultrasound video sequences. Quantifying fascicle behaviour is required to improve understanding of the functional significance of a muscle’s geometric properties. Ultrasound imaging provides a non-invasive means of capturing information on fascicle behaviour during dynamic movements, to date however computational approaches to assess such images are limited. Our approach to the problem is novel because we permit fascicles to take up non-linear shape configurations. We achieve this using a Bayesian tracking framework that is: i) robust, conditioning shape estimates on the entire history of image observations; and ii) flexible, enforcing only a very weak Gaussian Process shape prior that requires fascicles to be locally smooth. The method allows us to track and quantify fascicle behaviour in vivo during a range of movements, providing insight into dynamic changes in muscle geometric properties which may be linked to patterns of activation and intramuscular forces and pressures.