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超声图像显示的肌纤维运动自动检测方法

Automatic detection method of muscle fiber movement as revealed by ultrasound images.

作者信息

Miyoshi Tasuku, Kihara Tomohiko, Koyama Hiroyuki, Yamamoto Shin-ichiro, Komeda Takashi

机构信息

Shibaura Institute of Technology, 307 Fukasaku, Minuma-ku, Saitama-city, Saitama 3378570, Japan.

出版信息

Med Eng Phys. 2009 Jun;31(5):558-64. doi: 10.1016/j.medengphy.2008.11.004. Epub 2008 Dec 24.

Abstract

The objective of this study was to develop a method of muscle structure measurement based on the automatic analysis of muscle fibers, proximal fascias, and distal aponeurosis movements as revealed by a time-series of ultrasound images. This method was designed to detect changes in the length of muscle fiber movements, and its validity was demonstrated in a time-series of muscle movement, slow ankle dorsiflexion (10 degrees/s), by comparison to manual measurement. The results showed that, when this method was used, the changes in the length of the muscle fiber under slow muscle movement were smaller than those in manual operations by novice individuals. However, with the proposed method, it was possible to obtain a sufficient degree of validity and reliability for the changes in the length of the muscle fiber length compared with those in manual operations, since the correlation coefficients exceeded 0.8 which was tested by the linear regression. The proposed method suggests that automation reduces the errors caused by manual operations and makes the processing of data possible in an acceptable amount of time.

摘要

本研究的目的是开发一种基于超声图像时间序列所揭示的肌纤维、近端筋膜和远端腱膜运动自动分析的肌肉结构测量方法。该方法旨在检测肌纤维运动长度的变化,并通过与手动测量相比较,在肌肉运动(缓慢踝关节背屈,10度/秒)的时间序列中证明了其有效性。结果表明,使用该方法时,缓慢肌肉运动下肌纤维长度的变化比新手手动操作时的变化小。然而,与手动操作相比,采用所提出的方法能够获得足够的有效性和可靠性来测量肌纤维长度的变化,因为通过线性回归测试,相关系数超过了0.8。所提出的方法表明,自动化减少了手动操作引起的误差,并使在可接受的时间内处理数据成为可能。

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