Ali Rehman, Mitcham Trevor, Owolabi Israel, McConnell Sarah, Duric Nebojsa
Department of Imaging Sciences, University of Rochester, Rochester, New York 14642, USA.
Department of Electrical and Computer Engineering, University of Rochester, Rochester, New York 14642, USA.
JASA Express Lett. 2025 Jan 1;5(1). doi: 10.1121/10.0034763.
Ultrasound tomography fundamentally relies on low-frequency data to avoid cycle skipping in full-waveform inversion (FWI). In the absence of sufficiently low-frequency data, we can extrapolate low-frequency content from existing high-frequency signals by using the same approach used in frequency-difference beamforming. This low-frequency content is then used to kickstart FWI and avoid cycle skipping at higher frequencies. In simulations, the structural similarity index measure and peak signal-to-noise ratio of the reconstructed image improve by 0.28 and 8.6 dB, respectively, as a result of frequency differencing. Experiments show that internal structures can be seen with greater clarity because of frequency differencing.
超声层析成像从根本上依赖低频数据,以避免全波形反演(FWI)中的周期跳跃。在缺乏足够低频数据的情况下,我们可以通过使用与频差波束形成相同的方法,从现有的高频信号中推断出低频成分。然后,利用这种低频成分来启动全波形反演,并避免在较高频率下出现周期跳跃。在模拟中,频差使重建图像的结构相似性指数和峰值信噪比分别提高了0.28和8.6分贝。实验表明,由于频差,内部结构能够看得更清晰。