Groopman Amber M, Katz Jonathan I, Holland Mark R, Fujita Fuminori, Matsukawa Mami, Mizuno Katsunori, Wear Keith A, Miller James G
Department of Physics, Washington University in St. Louis, St. Louis, Missouri 63130, USA.
Department of Radiology and Imaging Sciences, Indiana University-Purdue University School of Medicine, Indianapolis, Indiana 46202, USA.
J Acoust Soc Am. 2015 Aug;138(2):594-604. doi: 10.1121/1.4923366.
Conventional, Bayesian, and the modified least-squares Prony's plus curve-fitting (MLSP + CF) methods were applied to data acquired using 1 MHz center frequency, broadband transducers on a single equine cancellous bone specimen that was systematically shortened from 11.8 mm down to 0.5 mm for a total of 24 sample thicknesses. Due to overlapping fast and slow waves, conventional analysis methods were restricted to data from sample thicknesses ranging from 11.8 mm to 6.0 mm. In contrast, Bayesian and MLSP + CF methods successfully separated fast and slow waves and provided reliable estimates of the ultrasonic properties of fast and slow waves for sample thicknesses ranging from 11.8 mm down to 3.5 mm. Comparisons of the three methods were carried out for phase velocity at the center frequency and the slope of the attenuation coefficient for the fast and slow waves. Good agreement among the three methods was also observed for average signal loss at the center frequency. The Bayesian and MLSP + CF approaches were able to separate the fast and slow waves and provide good estimates of the fast and slow wave properties even when the two wave modes overlapped in both time and frequency domains making conventional analysis methods unreliable.
将传统方法、贝叶斯方法以及改进的最小二乘 Prony 法加曲线拟合(MLSP + CF)方法应用于使用 1MHz 中心频率宽带换能器采集的数据,该数据来自单个马松质骨标本,该标本被系统地从 11.8mm 缩短至 0.5mm,共 24 个样本厚度。由于快波和慢波重叠,传统分析方法仅限于样本厚度为 11.8mm 至 6.0mm 的数据。相比之下,贝叶斯方法和 MLSP + CF 方法成功分离了快波和慢波,并为样本厚度从 11.8mm 至 3.5mm 提供了快波和慢波超声特性的可靠估计。对三种方法在中心频率处的相速度以及快波和慢波衰减系数的斜率进行了比较。在中心频率处的平均信号损失方面,三种方法之间也观察到了良好的一致性。即使两种波模式在时域和频域中都重叠,使得传统分析方法不可靠,贝叶斯方法和 MLSP + CF 方法仍能够分离快波和慢波,并对快波和慢波特性提供良好的估计。