Bahbah N, Novell A, Bouakaz A, Djelouah H
USTHB, Université des Sciences et de la Technologie Houari Boumediene, Faculté de Physique, BP 32 El Allia, Bab-Ezzouar, Alger, Algeria.
Université François Rabelais de Tours, Inserm U930, Imagerie et Cerveau, Tours, France.
Ultrasonics. 2017 Apr;76:200-207. doi: 10.1016/j.ultras.2017.01.009. Epub 2017 Jan 16.
The goal of this work is to exploit the statistical signatures for discrimination between biological tissues and contrast microbubbles in order to develop new strategies for contrast imaging and tissue characterization. For this purpose, the efficiency of the Nakagami statistical model, for describing the ultrasonic echoes of both contrast microbubbles and tissues, was investigated. Experimental measurements have been performed using a linear array probe connected to an open research platform. A commercially available in vitro phantom was used to mimic biological tissue in which SonoVue contrast microbubbles were flowing. Experimental ultrasound echoes have been filtered around the transmitted frequency (fundamental at 2.5MHz) and around twice the transmitted frequency (at 5MHz) for 2nd harmonic analysis, and a logarithmic compression was applied. The signals have been analyzed in order to evaluate the Nakagami parameter m, the scaling parameter Ω and the probability density function at both frequencies. Parametric images based on the Nakagami parameters map (Nakagami-mode images) were reconstructed and compared to B-mode images. Contrary to the B-mode image which is influenced by the system settings and user operations, the Nakagami parametric image is only based on the backscattered statistics of the ultrasonic signals in a local phantom. Such an imaging principle allows the Nakagami image to quantify the local scatterer concentrations in the phantom and to extract the backscattering information from the regions of the weakest echoes that may be lost in the conventional B-mode image. Results show that the tissue and microbubbles characterization is more sensitive in the 2nd harmonic mode when a logarithmic transform is used. These results would be useful for improving the ultrasound image quality and contrast detection in nonlinear mode.
这项工作的目标是利用统计特征来区分生物组织和造影微泡，以便开发造影成像和组织表征的新策略。为此，研究了用于描述造影微泡和组织超声回波的 Nakagami 统计模型的效率。使用连接到开放研究平台的线性阵列探头进行了实验测量。使用市售的体外模型来模拟有 SonoVue 造影微泡流动的生物组织。实验超声回波在发射频率（2.5MHz 基波）及其两倍频率（5MHz）附近进行滤波以进行二次谐波分析，并应用对数压缩。对信号进行分析以评估两个频率下的 Nakagami 参数 m、缩放参数 Ω 和概率密度函数。基于 Nakagami 参数图重建了参数图像（Nakagami 模式图像）并与 B 模式图像进行比较。与受系统设置和用户操作影响的 B 模式图像不同，Nakagami 参数图像仅基于局部模型中超声信号的反向散射统计。这种成像原理使 Nakagami 图像能够量化模型中的局部散射体浓度，并从传统 B 模式图像中可能丢失的最弱回波区域提取反向散射信息。结果表明，当使用对数变换时，组织和微泡表征在二次谐波模式下更敏感。这些结果将有助于提高非线性模式下的超声图像质量和造影剂检测。
