Estimating skeletal muscle fascicle curvature from B-mode ultrasound image sequences.

ABSTRACT: We address the problem of tracking in vivo muscle fascicle shape and length changes using ultrasound video sequences. Quantifying fascicle behavior is required to improve understanding of the functional significance of a muscle's geometric properties. Ultrasound imaging provides a noninvasive means of capturing information on fascicle behavior 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 nonlinear shape configurations. We achieve this using a Bayesian tracking framework that is: 1) robust, conditioning shape estimates on the entire history of image observations; and 2) flexible, enforcing only a very weak Gaussian Process shape prior that requires fascicles

SUBMITTER: Darby J 

PROVIDER: S-EPMC3768108 | biostudies-literature | 2013 Jul

REPOSITORIES: biostudies-literature