Biolab, Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy.
Biolab, Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy; Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
Ultrasound Med Biol. 2019 Mar;45(3):672-683. doi: 10.1016/j.ultrasmedbio.2018.11.012. Epub 2019 Jan 9.
Ultrasonography allows non-invasive and real time-measurement of the visible cross-sectional area (CSA) of muscles, which is a clinically relevant descriptor of muscle size. The aim of this study was to develop and validate a fully automatic method called transverse muscle ultrasound analysis (TRAMA) for segmentation of the muscle in B-mode transverse ultrasound images and measurement of muscle CSA. TRAMA was tested on a database of 200 ultrasound images of the rectus femoris, vastus lateralis, tibialis anterior and medial gastrocnemius muscles. The automatic CSA measurements were compared with manual measurements obtained by two operators. There were no statistical differences between the automatic and manual measurements of CSA of the four muscles, and TRAMA performance was comparable to intra-operator variability in terms of the Dice similarity coefficient and Hausdorff distance between the automatic and manual segmentations. Compared with manual segmentation, the Dice similarity coefficient for the proposed method was always higher than 93%; the Hausdorff distance never exceeded 4 mm, and the maximum absolute error was 62 mm. TRAMA is the first automated algorithm that analyzes and segments ultrasound scans of the muscle in the transverse plane. It can be adopted in future studies for automatic segmentation of muscle regions of interest to enhance and automatize a multitexture analysis of muscle structure.
超声成像是一种非侵入性的实时测量方法,可以测量肌肉的可见横截面积(CSA),这是肌肉大小的一个具有临床意义的描述符。本研究旨在开发和验证一种名为横断肌肉超声分析(TRAMA)的全自动方法,用于对 B 模式横断超声图像中的肌肉进行分割和测量 CSA。TRAMA 在 200 张股直肌、股外侧肌、胫骨前肌和内侧比目鱼肌的超声图像数据库上进行了测试。自动 CSA 测量值与由两名操作员获得的手动测量值进行了比较。四种肌肉的自动和手动 CSA 测量值之间没有统计学差异,并且就 Dice 相似系数和自动与手动分割之间的 Hausdorff 距离而言,TRAMA 的性能与操作员内变异性相当。与手动分割相比,该方法的 Dice 相似系数始终高于 93%;Hausdorff 距离从不超过 4 毫米,最大绝对误差为 62 毫米。TRAMA 是第一个分析和分割横断平面肌肉超声扫描的自动算法。它可以在未来的研究中用于自动分割感兴趣的肌肉区域,以增强和自动化对肌肉结构的多纹理分析。