用随机方法加速乳腺超声断层成像，速度与传统方法相当但快一倍以上
Stochastic Reconstruction of the Speed of Sound in Breast Ultrasound Computed Tomography with Phase Encoding in the Frequency Domain
- 在频域中引入相位编码的随机反演方法
- 2D/3D仿真和实验数据验证，质量与确定性方法相当
- 结合多超波束与随机集合，重建时间减少一半以上
超声计算机断层成像（USCT）作为一种安全、无操作者依赖的乳腺成像技术近年重新兴起。当前最先进的图像重建方法基于频域内的确定性优化算法，在300 kHz–1 MHz带宽下实现。已有研究尝试时域中的确定性与随机优化算法。本文提出频域中等效的随机反演（相位编码），聚焦声速重建。在二维与三维合成数据上测试该算法，明确区分逆犯罪与非逆犯罪场景，并与确定性反演对比。随后在实验数据上展示频域随机反演的效果。通过利用多重超波束与随机集合概念，提供了有力证据：基于相位编码的频域随机重建在声速成像质量上与确定性方法基本相当，且重建时间显著缩短超过一半。
原文摘要 · Abstract (English)
The framework of ultrasound computed tomography (USCT) has recently re-emerged as a powerful, safe and operator-independent way to image the breast. State of the art image reconstruction methods are performed with iterative techniques based on deterministic optimization algorithms in the frequency domain in the 300 kHz - 1 MHz bandwidth. Alternative algorithms with deterministic and stochastic optimization have been considered in the time-domain. In this paper, we present the equivalent stochastic inversion in the frequency domain (phase encoding), with a focus on reconstructing the speed of sound. We test the inversion algorithm on synthetic data in 2D and 3D, by explicitly differentiating between inverse crime and non-inverse crime scenarios, and compare against the deterministic inversion. We then show the results of the stochastic inversion in the frequency domain on experimental data. By leveraging on the concepts of multiple super-shots and stochastic ensembles, we provide robust evidence that image quality of a stochastic reconstruction of the speed of sound with phase encoding in the frequency domain is comparable, and essentially equivalent, to the one of a deterministic reconstruction, with the further benefit of drastically reducing reconstruction times by more than half.
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