Large-Domain, Low-Contrast Acoustic Inverse Scattering for Ultrasound Breast Imaging

We present a full-wave acoustic inverse-scattering algorithm designed specifically for ultrasonic breast imaging. At ultrasonic frequencies, the image domain is roughly tens to hundreds of lambda(min) cubed, where lambda(min) is the smallest wavelength in the transmit signal spectrum. The expected range of contrasts for the breast imaging problem for density, compressibility, and compressive loss is +/- 20% of the background. Because of the low contrast, Born iterations provide the basic structure of the inverse-scattering algorithm. However, we use a multiobjective covariance-based least squares cost function in place of the basic least squares cost function to estimate the contrast functions. This cost function provides physically meaningful regularization based on a priori knowledge of the contrasts. Also, due to the size of the imaging domain and because the objects to be imaged are low contrast and inhomogeneous, we use the Neumann series solution as the forward solver. The largest domain imaged in simulation was 50 lambda(min) X 50 lambda(min) in 2-D.