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Simple Muscle Architecture Analysis (SMA): An ImageJ macro tool to automate measurements in B-mode ultrasound scans

机译:简单的肌肉架构分析(SMA):IMAGEJ宏工具,用于自动化B模式超声扫描中的测量

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In vivo measurements of muscle architecture (i.e. the spatial arrangement of muscle fascicles) are routinely included in research and clinical settings to monitor muscle structure, function and plasticity. However, in most cases such measurements are performed manually, and more reliable and time-efficient automated methods are either lacking completely, or are inaccessible to those without expertise in image analysis. In this work, we propose an ImageJ script to automate the entire analysis process of muscle architecture in ultrasound images: Simple Muscle Architecture Analysis (SMA). Images are filtered in the spatial and frequency domains with built-in commands and external plugins to highlight aponeuroses and fascicles. Fascicle dominant orientation is then computed in regions of interest using the OrientationJ plugin. Bland-Altman plots of analyses performed manually or with SMA indicate that the automated analysis does not induce any systematic bias and that both methods agree equally through the range of measurements. Our test results illustrate the suitability of SMA to analyse images from superficial muscles acquired with a broad range of ultrasound settings.
机译:在肌肉建筑的体内测量(即肌肉束的空间排列)通常包括在研究和临床环境中,以监测肌肉结构,功能和可塑性。然而,在大多数情况下,手动执行这种测量,并且可以完全缺乏更可靠和更有效的自动化方法,或者在没有图像分析中的专业知识的情况下无法访问。在这项工作中,我们提出了一个imagej脚本,以自动化超声图像中的肌肉架构的整个分析过程:简单的肌肉架构分析(SMA)。在具有内置命令和外部插件的空间和频率域中过滤图像,以突出显示腱膜和束。然后,使用OrientationJ插件在感兴趣的区域中计算Fascicle主导定位。手动或使用SMA进行的分析的平坦 - altman图表明自动化分析不会引起任何系统偏差,并且两种方法都同意通过测量范围。我们的测试结果说明了SMA的适用性,分析了通过广泛超声设置所获得的浅表肌肉的图像。

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