简单肌肉结构分析（SMA）：一个ImageJ宏工具，用于在B型超声扫描中自动测量
Simple Muscle Architecture Analysis (SMA): an ImageJ macro tool to automate measurements in B-mode ultrasound scans
摘要：
肌肉结构（即肌肉束的空间排列）的体内测量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，这种测量是手动进行的，更可靠和更省时的自动化方法要么完全缺乏，要么是那些没有图像分析专业知识的人无法获得的。在这项工作中，我们提出了一个ImageJ脚本来自动化超声图像中肌肉结构的整个分析过程：简单肌肉结构分析（SMA）。通过内置命令和外部插件在空间和频率域对图像进行过滤，以突出显示腱膜和纤维束。然后使用OrientationJ插件计算感兴趣区域中的束优势方向。手动或使用SMA进行的分析的Bland-Altman图表明，自动分析不会引起任何系统偏倚，并且两种方法在测量范围内一致。我们的测试结果说明了SMA的适用性，以分析图像从浅表肌肉获得了广泛的超声设置。
英文摘要：
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 indicates 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.
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