Title: Ultrasound Matrix Imaging-Part I: The focused reflection matrix, the F-factor and the role of multiple scattering Show Chinese title

Title: 超声矩阵成像-第一部分：聚焦反射矩阵、F因子以及多次散射的作用

Abstract: This is the first article in a series of two dealing with a matrix approach for aberration quantification and correction in ultrasound imaging. Advanced synthetic beamforming relies on a double focusing operation at transmission and reception on each point of the medium. Ultrasound matrix imaging (UMI) consists in decoupling the location of these transmitted and received focal spots. The response between those virtual transducers form the so-called focused reflection matrix that actually contains much more information than a confocal ultrasound image. In this paper, a time-frequency analysis of this matrix is performed, which highlights the single and multiple scattering contributions as well as the impact of aberrations in the monochromatic and broadband regimes. Interestingly, this analysis enables the measurement of the incoherent input-output point spread function at any pixel of this image. A fitting process enables the quantification of the single scattering, multiple scattering and noise components in the image. From the single scattering contribution, a focusing criterion is defined, and its evolution used to quantify the amount of aberration throughout the ultrasound image. In contrast to the state-of-the-art coherence factor, this new indicator is robust to multiple scattering and electronic noise, thereby providing a contrasted map of the focusing quality at a much better transverse resolution. After a validation of the proof-of-concept based on time-domain simulations, UMI is applied to the in-vivo study of a human calf. Beyond this specific example, UMI opens a new route for speed-of-sound and scattering quantification in ultrasound imaging. Show Chinese abstract

Abstract: 这是关于超声成像中像差量化和校正的矩阵方法系列文章中的第一篇。 先进的合成波束形成依赖于在介质每个点上的发射和接收时的双重聚焦操作。 超声矩阵成像（UMI）在于解耦这些发射和接收焦点的位置。 这些虚拟换能器之间的响应形成了所谓的聚焦反射矩阵，该矩阵实际上包含比共焦超声图像更多的信息。 在本文中，对该矩阵进行了时频分析，这突显了单次和多次散射贡献以及单色和宽带情况下像差的影响。 有趣的是，这种分析使得能够在该图像的任何像素处测量非相干输入输出点扩散函数。 拟合过程使得能够量化图像中的单次散射、多次散射和噪声成分。 从单次散射贡献中定义了一个聚焦准则，并利用其变化来量化超声图像中像差的数量。 与现有的相干因子不同，这个新指标对多次散射和电子噪声具有鲁棒性，从而提供了一种对比度更高的聚焦质量图，且横向分辨率更高。 在基于时域仿真的概念验证验证之后，UMI被应用于人体小腿的在体研究。 除了这个具体例子外，UMI为超声成像中的声速和散射量化开辟了一条新的途径。