Automated regional analysis of B-mode ultrasound images of skeletal muscle movement.
Automated regional analysis of B-mode ultrasound images of skeletal muscle movement.
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DOI：
10.1152/japplphysiol.00701.2011
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发表时间：
2012-01
期刊：
影响因子：
--
通讯作者：
Loram ID
中科院分区：
文献类型：
--
作者：
Darby J;Hodson-Tole EF;Costen N;Loram ID
为了理解骨骼肌解剖学的功能意义，需要一种量化不同组织结构在动态任务中局部形状变化的方法。利用b型超声成像良好的空间和时间分辨率，我们描述了一种自动将图像分割成束膜和腱膜区域，并在每个组织的局部部分独立跟踪特征运动的方法。在踝关节旋转（2°和20°）、等距收缩（1、5和50 Nm）和深膝关节弯曲时，收集8名参与者的腓肠肌内侧超声图像（25 Hz）。使用Kanade-Lucas-Tomasi特征跟踪器来识别和跟踪图像序列中任何显著和持久的特征。然后发现局部运动的速度场表示，并使用多分辨率活动形状模型（ASM）的分割在束膜和腱膜区域之间进行细分。通过在一组探针上插值场的效果来量化每个区域的运动。ASM分割结果与手工标记的数据进行比较，而腱膜和肌束运动的结果则与先前记录的相互关联方法进行比较。ASM提供了良好的图像分割（平均误差<1 mm），可以对来自7个参与者的序列进行全自动初始化。特征跟踪在小运动中提供了与相互关联方法相似的长度变化结果，而在大运动中表现优于相互关联方法。所提出的方法提供了在不同运动/条件下区分肌肉形状和模型应变分布的主动和被动变化的潜力，并量化沿腱膜的非均匀应变。
To understand the functional significance of skeletal muscle anatomy, a method of quantifying local shape changes in different tissue structures during dynamic tasks is required. Taking advantage of the good spatial and temporal resolution of B-mode ultrasound imaging, we describe a method of automatically segmenting images into fascicle and aponeurosis regions and tracking movement of features, independently, in localized portions of each tissue. Ultrasound images (25 Hz) of the medial gastrocnemius muscle were collected from eight participants during ankle joint rotation (2° and 20°), isometric contractions (1, 5, and 50 Nm), and deep knee bends. A Kanade-Lucas-Tomasi feature tracker was used to identify and track any distinctive and persistent features within the image sequences. A velocity field representation of local movement was then found and subdivided between fascicle and aponeurosis regions using segmentations from a multiresolution active shape model (ASM). Movement in each region was quantified by interpolating the effect of the fields on a set of probes. ASM segmentation results were compared with hand-labeled data, while aponeurosis and fascicle movement were compared with results from a previously documented cross-correlation approach. ASM provided good image segmentations (<1 mm average error), with fully automatic initialization possible in sequences from seven participants. Feature tracking provided similar length change results to the cross-correlation approach for small movements, while outperforming it in larger movements. The proposed method provides the potential to distinguish between active and passive changes in muscle shape and model strain distributions during different movements/conditions and quantify nonhomogeneous strain along aponeuroses.
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DOI：
10.1046/j.1365-201x.2003.01048.x
发表时间：
2003-02-01
期刊：
ACTA PHYSIOLOGICA SCANDINAVICA
影响因子：
--
作者：
Magnusson, SP;Hansen, P;Kjaer, M
通讯作者：
Kjaer, M
影响因子：
3.3
作者：
Higham, Timothy E.;Biewener, Andrew A.;Wakeling, James M.
通讯作者：
Wakeling, James M.
影响因子：
10.6
作者：
Mikic, I;Krucinski, S;Thomas, JD
通讯作者：
Thomas, JD
影响因子：
10.6
作者：
Bosch, JG;Mitchell, SC;Reiber, JHC
通讯作者：
Reiber, JHC
影响因子：
2.4
作者：
Namburete, Ana I. L.;Rana, Manku;Wakeling, James M.
通讯作者：
Wakeling, James M.