基于超声弹性成像的生物组织弹性水平估计算法

J. J. Diaz, N. P. Castellanos, C. Pineda, C. Hernández, L. Ventura, J. Gutierrez
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引用次数: 1

摘要

本文提出了一种基于超声弹性成像图像的生物组织弹性评估算法,以提高诊断能力。将该算法应用于4名健康受试者的RGB图像;包括预处理、滤波、兴趣区域选择、分割和像素计算等阶段。采用基于平均和极差技术的重复性和再现性方法(R&R)对该方法进行了验证。在这项测试中,两位医生在同一时间从同一解剖区域的同一受试者获得了美国弹性成像图像。对三种颜色贴图进行插值后得到弹性图。根据R&R指南,每个平面(红、绿、蓝)的可重复性和再现性的结果小于10%。这些结果表明该算法具有良好的性能。这一建议代表了一个有希望的诊断工具,客观地评估生物组织的弹性,用于诊断,治疗随访和研究目的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Algorithm to estimate the level of elasticity of biological tissue with ultrasound elastography images
The paper presents an algorithm to evaluate the elasticity of biological tissues from an ultrasound acquired elastography images to enhance the diagnostic capabilities. The algorithm was applied to RGB images of four healthy subjects; including pre-processing, filtering, region of interest selection, segmentation and pixel computing stages. A Repeatability and Reproducibility method (R&R) based on average and range technique is used to validate the procedure. For this test, two physicians acquired the US elastography images from the same subjects in the same anatomic region, at the same time. An elastometry graph is obtained after interpolation of the three color maps is applied. According R&R guidelines, the results for repeatability and reproducibility for each plane (red, green and blue) were less to 10%. These results are indicative of an algorithm with good performance. This proposal represents a promising diagnostic tool to evaluate objectively the elasticity of biological tissue for diagnostic, treatment follow-up and research purposes.
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