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Title: Estimating skeletal muscle fascicle curvature from B-mode ultrasound image sequences
Authors: Darby, John
Li, Baihua
Costen, Nicholas
Loram, Ian
Hodson-Tole, Emma
Keywords: Image analysis
Importance sampling
Medical imaging
Particle filtering
Issue Date: 2013
Publisher: © IEEE
Citation: DARBY, J. ... et al, 2013. Estimating skeletal muscle fascicle curvature from B-mode ultrasound image sequences. IEEE Transactions on Biomedical Engineering, 60 (7), pp.1935-1945
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 to be locally smooth. The method allows us to track and quantify fascicle behavior 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.
Description: This is the accepted manuscript version of the paper. © 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Version: Accepted for publication
DOI: 10.1109/TBME.2013.2245328
URI: https://dspace.lboro.ac.uk/2134/20257
Publisher Link: http://dx.doi.org/10.1109/TBME.2013.2245328
ISSN: 0018-9294
Appears in Collections:Conference Papers and Presentations (Computer Science)

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