The H-scan approach to classifying ultrasound echoes

传统的B超图像将接收到的回波的包络显示为灰度图像。回声 是由发生声阻抗变化的镜面反射和散射部位产生的。一个很长的- 感兴趣的区域关注来自不同区域的背向散射超声的频率依赖性 纸巾。一些高级的后向散射分析估计了频率相关性和角度相关性 后向散射波。然而，大多数统计平均技术都需要一些感兴趣的区域 计算散射参数的期望值。不幸的是，超声波的不利统计数据 回波会限制这些估计器的空间分辨率或精度。病理上的特定变化可能会导致 组织的基本大小、结构和组成的变化，因此以某种方式捕捉这些 变化依然存在。我们假设一种新的使用匹配Hermite函数的匹配滤波方法可以 以高分辨率对主要散射类别进行分类和可视化。这使临床医生能够分辨出微妙的 原本看起来相似的细胞和实质变化，从而增加了新的和相关的 将信息发送到诊断超声。最近导出的H扫描是一种新的方法，其中接收到的回波 可以与来自组织的三种主要回声相关联。回声与高斯的数学有关 加权Hermite多项式，可以简化整体识别任务。生成的图像为 表示为H扫描，其中‘H’表示Hermite或色相，因为通过色调进行的识别不同于 传统的B超检查。该框架在生物组织-肝脏和胎盘-中进行了初步测试 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， H型扫描必须在一定深度范围内的组织内显示出一致的结果，并且尽管存在衰减。 其次，必须证明H扫描对组织散射体的细胞和亚细胞变化很敏感， 与临床上有意义的疾病相关的。这个项目将解决这两个问题。深度和深度 衰减依赖关系将在一系列体模和组织实验中进行研究和校正。这个 敏感性和准确性将在大鼠肝脏脂肪变性模型中进行测试。结果应该确定关键 H-Scan的性能问题，从而表征其改进诊断超声成像的能力 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.