Smith Cameron A B, Toulemonde Matthieu, Lerendegui Marcelo, Riemer Kai, Malounda Dina, Weinberg Peter D, Shapiro Mikhail G, Tang Meng-Xing
Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, USA; Department of Bioengineering, Imperial College London, London, UK.
Department of Bioengineering, Imperial College London, London, UK; Department of Earth Science and Engineering, Imperial College London, London, UK.
Ultrasound Med Biol. 2025 Sep;51(9):1523-1528. doi: 10.1016/j.ultrasmedbio.2025.05.023. Epub 2025 Jun 28.
Ultrasound imaging as a clinical tool is commonly achieved using the delay and sum (DAS) beamforming algorithm, which has limited resolution and suffers from high side lobes. Recently nonlinear processing has proven to be an effective way to enhance image quality. In this work, we describe a new beamforming algorithm called Cross-Angular Delay Multiply and Sum (CADMAS).
CADMAS takes advantage of nonlinear compounding across planewave steering angles to enhance image contrast. This is then implemented with a mathematical reformulation to produce images at a low computational cost. We tested CADMAS in both conventional B-Mode and amplitude modulation imaging across in vitro and in vivo datasets, and for microbubbles and gas vesicles. We compared the results to DAS and two other nonlinear beamformers, frame multiply and sum (FMAS) and delay multiply and sum (DMAS), as well as the combination of the two.
Our results show on average across our datasets a 7.6 to 40 dB improvement in image contrast over DAS and a 4.8 to 20 dB improvement over DMAS. The computation time of CADMAS is between 1 and 2 times that of DAS; in our implementation we experienced a less than 6% increase in computation time.
Our results show a robust improvement in contrast across multiple datasets both in vitro and in vivo, demonstrating its potential for biological and clinical applications.
超声成像作为一种临床工具，通常使用延迟求和（DAS）波束形成算法来实现，该算法分辨率有限且存在高旁瓣问题。最近，非线性处理已被证明是提高图像质量的有效方法。在这项工作中，我们描述了一种名为交叉角延迟相乘求和（CADMAS）的新波束形成算法。
CADMAS利用平面波 steering 角上的非线性复合来增强图像对比度。然后通过数学重新表述来实现，以低计算成本生成图像。我们在体外和体内数据集的传统 B 模式和幅度调制成像中对 CADMAS 进行了测试，包括微泡和气体囊泡。我们将结果与 DAS 以及另外两种非线性波束形成器——帧相乘求和（FMAS）和延迟相乘求和（DMAS），以及两者的组合进行了比较。
我们的结果表明，在我们的数据集上，与 DAS 相比，图像对比度平均提高了 7.6 至 40 dB，与 DMAS 相比提高了 4.8 至 20 dB。CADMAS 的计算时间是 DAS 的 1 到 2 倍；在我们的实现中，计算时间增加不到 6%。
我们的结果表明，在体外和体内的多个数据集中，对比度都有显著提高，证明了其在生物学和临床应用中的潜力。
