The H-scan approach to classifying ultrasound echoes

传统的超声 B 扫描图像将接收回波的包络显示为灰度图像。回声 由声阻抗发生变化的镜面反射和散射位置产生。一个长- 感兴趣的站立区域涉及来自不同内部的反向散射超声波的频率依赖性 组织。一些先进的反向散射分析估计了频率依赖性和角度依赖性 后向散射波。然而，大多数统计平均技术需要一些感兴趣的区域 计算散射参数的期望值。不幸的是，超声的不利统计数据 回声会限制这些估计器的空间分辨率或准确性。病理学的特定变化可能导致 组织的基本尺寸、结构和成分发生变化，因此以某种方式捕获这些变化的目标 变化依然存在。我们假设使用匹配 Hermite 函数的新匹配滤波器方法可以 以高分辨率对主要散射类别进行分类和可视化。这使得临床医生能够区分微妙的 细胞和实质变化，否则会显得相似，从而增加新的和相关的 超声诊断信息。最近衍生的 H 扫描是一种新方法，其中接收到的回波 可以与来自组织的三大类回声联系起来。回声与高斯数学有关 加权埃尔米特多项式使得整体识别任务得以简化。结果图像是 表示为 H 扫描，其中“H”代表 Hermite 或色调，因为色调的识别与 传统的 B 扫描。该框架在生物组织（肝脏和胎盘）中进行了初步测试，其中 组织 H 扫描图像的变化似乎与小散射体浓度的变化有关。 然而，为了将 H 扫描确立为一种可行的诊断技术，必须证明两个问题。首先， 尽管有衰减，H 扫描必须能够在一定深度范围内的组织内提供一致的结果。 其次，必须证明 H 扫描对组织散射体中的细胞和亚细胞变化敏感， 与具有临床意义的病症相关。该项目将解决这两个问题。深度和 衰减依赖性将在一系列模型和组织实验中进行研究和纠正。的 将在大鼠肝脏脂肪变性模型中测试敏感性和准确性。结果应确定关键 H 扫描的性能问题，从而表征其推进超声诊断成像的能力 评估人类的病理学。

Traditional ultrasound B-Scan images show the envelope of received echoes as a grey scale image. The echoes are produced from specular reflections and scattering sites where changes in acoustic impedance occur. A long- standing area of interest concerns the frequency dependence of backscattered ultrasound from within different tissues. Some advanced backscatter analyses estimate the frequency dependence and angular dependence of backscattered waves. However, most statistical averaging techniques require some region of interest over which to calculate the expected value of scattering parameters. Unfortunately, the unfavorable statistics of ultrasound echoes can limit the spatial resolution or accuracy of these estimators. Specific changes in pathology can cause changes in the underlying size, structure, and composition of tissue, and so the goal of somehow capturing these changes remains. We hypothesize that a new matched filter approach using matched Hermite functions can classify and visualize major scattering classes at high resolution. This enables clinicians to distinguish subtle cellular and parenchymal changes that would otherwise appear similar, thereby adding new and relevant information to diagnostic ultrasound. The recently derived H-scan is a fresh approach where the received echoes can be linked to three major classes of echoes from tissues. Echoes are linked to the mathematics of Gaussian Weighted Hermite Polynomials so that the overall identification task can be simplified. The resulting images are denoted as H-scans, where ‘H’ represents Hermite or hue, since the identification by hue is distinct from the traditional B-scan. The framework was given an initial test in biological tissues – liver and placenta – where changes in tissue H-scan images are plausibly linked to changes in the concentration of small scatterers. However, in order to establish H-Scan as a viable diagnostic technique, two issues must be proven. First, the H-scan must be shown to give consistent results within tissues over a range of depths and despite attenuation. Second, the H-scan must be shown to be sensitive to cellular and sub-cellular changes in tissue scatterers, relevant to a clinically significant condition. This project will address both these issues. The depth and attenuation dependence will be studied and corrected in a series of phantom and tissue experiments. The sensitivity and accuracy will be tested in a liver steatosis model in rats. The results should establish the key performance issues for H-scan, and thereby characterize its ability to advance diagnostic ultrasound imaging for assessing pathology in humans.