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Continuous thickness measurement of rectus femoris muscle in ultrasound image sequences: A completely automated approach

机译:超声图像序列中股直肌的连续厚度测量:一种完全自动化的方法

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摘要

Muscle thickness 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 non-invasively study the thickness of human muscles as a reliable method. However, the measurement is traditionally conducted by manual digitization of reference points at the superior and inferior muscle fascias, thus it is subjective and time-consuming. In this paper, a novel method is proposed to detect the muscle thickness automatically. The superficial and deep fascias of a muscle are detected by line detection algorithm at the first ultrasound frame, and the image regions of interest (ROI) for the fascias are subsequently located and tracked by optical flow technique. The muscle thickness is geometrically obtained based on the location of the fascias for each frame. Six ultrasound sequences (250 frames in each sequence) are used to evaluate this method. The correlation coefficient of the detection results between the proposed method and manual method is 0.95 ± 0.01, and the difference is -0.05 ± 0.22 mm. The linear regression of the total 1500 detections show that a good linear correlation between the results of the two methods is obtained (R~2 = 0.981). The automated method proposed here provides an accurate, high repeatable and efficient approach for estimating fascicle thickness during human motion, thus justifying its application in biological sciences.
机译:在诊断和康复评估中,肌肉厚度是量化肌肉功能最广泛使用的参数之一。超声成像已被广泛用作非侵入性研究人体肌肉厚度的可靠方法。但是,传统上是通过手动数字化上,下肌肉筋膜上的参考点进行测量的,因此这是主观的且耗时的。本文提出了一种自动检测肌肉厚度的新方法。在第一超声帧处通过线检测算法来检测肌肉的浅筋膜和深筋膜,随后通过光流技术定位和跟踪筋膜的感兴趣图像区域(ROI)。肌肉厚度是基于每个帧的筋膜的位置以几何方式获得的。六个超声序列(每个序列250帧)用于评估此方法。所提出的方法与手动方法之间的检测结果的相关系数为0.95±0.01,相差为-0.05±0.22 mm。总共1500次检测的线性回归表明,两种方法的结果之间具有良好的线性相关性(R〜2 = 0.981)。这里提出的自动方法提供了一种精确,高度可重复且有效的方法,用于估计人体运动过程中的束厚度,从而证明了其在生物科学中的应用合理性。

著录项

  • 来源
    《Biomedical signal processing and control》 |2013年第6期|792-798|共7页
  • 作者单位

    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, China;

    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, China;

    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, China;

    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, China;

    Department of Biomedical Engineering, School of Medicine, Shenzhen University, Nanhai Ave 3688, Shenzhen, Guangdong 518052,China;

    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, China;

    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, China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Muscle thickness; Continuous measurement; Ultrasound image; Optical flow;

    机译:肌肉厚度;连续测量;超声图像;光流;

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