Nonlinear compressibility and mass density reconstruction under plane wave excitation using raw data with noise

Abstract

While linear pulse-echo ultrasound imaging methods (e.g. B-mode (BM), delay-and-sum (DAS) beamforming, synthetic aperture focusing technique (SAFT), filtered backpropagation (FBP), etc.) solely reach qualitative images mainly showing tissue boundaries assuming single scattering, nonlinear diffraction tomographic reconstruction methods have been proposed to reconstruct quantitative distributions of various acoustic tissue parameters as attenuation, compressibility, mass density or speed of sound under multiple scattering. In the present contribution, we analyze numerically the image reconstruction robustness of a previously suggested nonlinear simultaneous compressibility and mass density reconstruction algorithm under plane wave excitation to raw data with various noise levels. The image reconstruction results obtained for an unidirectional pulse-echo breast imaging application using raw data sets with maximum signal-to-noise ratios (SNRs) of 30 dB, 40 dB, 50 dB and 60 dB demonstrate the method's robustness up to 50 dB.