title: Continuous detection of muscle aspect ratio using keypoint tracking in ultrasonography.
abstract: Muscle aspect ratio of cross-sectional area 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 noninvasively study the characteristics of human muscles as a reliable method. However, the aspect ratio measurement is traditionally conducted by the manual digitization of reference points; thus, it is subjective, time-consuming, and prone to errors. In this paper, a novel method is proposed to continuously detect the muscle aspect ratio. Two keypoint pairs are manually digitized on the lateral and longitudinal borders at the first frame, and automatically tracked by an optical flow technique at the subsequent frames. The muscle aspect ratio is thereby obtained based on the estimated muscle width and thickness. Six ultrasound sequences from different subjects are used to evaluate this method, and the overall coefficient of multiple correlation of the results between manual and proposed methods is 0.97 ± 0.02. The linear regression shows that a good linear correlation between the results of the two methods is obtained (R(2) = 0.974), with difference -0.01 ± 0.16. The method proposed here provides an accurate, high repeatable, and efficient approach for estimating muscle aspect ratio during human motion, thus justifying its application in biological sciences.
authors.affiliation: National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Department of Biomedical Engineering, School of Medicine, Shenzhen University, Shenzhen 518060, China. lql@szu.edu.cn
authors.forename: Qiaoliang
authors.initials: Q
authors.lastname: Li
authors.forename: Huisheng
authors.initials: H
authors.lastname: Zhang
authors.forename: Suwen
authors.initials: S
authors.lastname: Qi
authors.forename: Mingbo
authors.initials: M
authors.lastname: Qiu
authors.forename: Xin
authors.initials: X
authors.lastname: Chen
authors.forename: Siping
authors.initials: S
authors.lastname: Chen
authors.forename: Tianfu
authors.initials: T
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D019412:Anatomy, Cross-Sectional / Q000379:methods*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D009119:Muscle Contraction / Q000502:physiology*; D018482:Muscle, Skeletal / Q000000981:diagnostic imaging* / Q000502:physiology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014463:Ultrasonography / Q000379:methods*