Speaker
Description
Speed-of-sound (SoS) inhomogeneities in tissue induce aberrations that degrade the quality of conventional ultrasound images. These aberrations, however, can be exploited to map the SoS, the key parameter governing wave propagation and a promising biomarker for breast cancer detection. Inspired by seismic full-waveform inversion, we present a pulse-echo SoS tomography approach with three main components. First, it builds on reflection matrix imaging, which is a redatuming operation that yields the impulse responses between virtually relocated transducers at arbitrary depths inside the medium. Correlations between these responses are then used to quantify the phase distortions experienced by the incident and reflected wavefronts across the entire field of view. Second, wave propagation in heterogeneous media is modeled by numerically solving a paraxial form of the wave equation via the Fourier split‑step technique. This accounts for complex wave phenomena, including diffraction and refraction, during matrix imaging while remaining computationally efficient. Third, the SoS distribution is estimated by minimizing the measured phase aberrations, whose exact sensitivities to SoS are computed using the adjoint-state method. This involves an adjoint matrix-imaging step in which aberrations are propagated upward in depth and correlated with the downward-propagated wavefields. The resulting inverse problem is solved iteratively using a BFGS quasi-Newton algorithm. We validate the method on experimental tissue-mimicking phantoms and demonstrate its performance in vivo for breast cancer detection. Importantly, the method naturally yields aberration-corrected images as part of the iterative process.