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

机译:超声检查中胫骨前肌厚度的实时估计

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Muscle thickness is an important parameter related to musculoskeletal 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相关的重要参数,并以多种方式和各种目的进行了研究。近年来,超声成像已广泛用于造成非侵入性的人肌肉的肌肉性质,具有实时和低成本的优点。通常手动测量肌厚度,这是主观和耗时的。此外,很少有关于动态收缩期间肌厚的自动估计的研究。在本研究中,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期间胫骨前肌的厚度变化。将所提出的方法的性能进行比较,使用来自十名患者的胫骨前肌的临床图像进行手动检测。结果,我们发现所提出的方法与手动测量很好地同意,并且它能够提供一种准确和有效的方法,用于估计人类运动期间的肌肉厚度。

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