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Real-Time Estimation of Tibialis Anterior Muscle Thickness from Dysfunctional Lower Limbs Using Sonography

机译:声像图实时估计功能异常的下肢胫骨前肌厚度

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Muscle thickness is an important parameter related to musculoskelet-al functions and has been studied in many ways and for various purposes. In recent years, ultrasound imaging has been widely used for measuring muscle properties of human muscles non-invasively, with the advantages of real time and low cost. The muscle thickness is usually measured manually, which is subjective and time consuming. In addition, there are few studies on automatic estimation of muscle thickness during dynamic contraction. In this study, an automatic estimation method based on compressive tracking algorithm is proposed to detect the thickness changes of tibialis anterior muscle during dynamic contraction on ultrasound images. The performance of the proposed method is compared to manual detection using clinical images from tibialis anterior muscles of ten patients. As a result, we found that the proposed method agrees well with the manual measurement, and it was able to provide an accurate and efficient approach for estimating muscle thickness during human motion.
机译:肌肉厚度是与肌肉骨骼功能有关的重要参数,并且已经以多种方式和出于各种目的进行了研究。近年来,超声成像已被广泛用于非侵入性地测量人体肌肉的肌肉特性,其具有实时性和低成本的优点。肌肉厚度通常是手动测量的,这是主观的且耗时的。另外,关于动态收缩过程中肌肉厚度的自动估计的研究很少。本研究提出了一种基于压缩跟踪算法的自动估计方法,以检测超声图像动态收缩过程中胫骨前肌的厚度变化。所提方法的性能与使用十名患者胫骨前肌的临床图像进行手动检测相比较。结果,我们发现所提出的方法与手动测量非常吻合,并且能够为估算人体运动过程中的肌肉厚度提供准确而有效的方法。

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