Ultrasound computed tomography (USCT) is a non-invasive quantitative imaging technique that estimates the reflectivity, sound speed, and attenuation properties of the imaged medium by transmitting and receiving ultrasound waves through multiple transducers, offering a cost-effective approach to medical imaging. Time-reversal imaging (TRI), based on the full two-way wave equation, provides effective illumination for steeply dipping structures and complex regions with strong vertical and lateral velocity contrasts. Applied to USCT, TRI enables the recovery of sub-Fresnel-scale fine structures without requiring iterative inversion or MHz-level high-frequency wavelets, thereby improving both image clarity and computational efficiency. However, the conventional zero-lag cross correlation imaging condition introduces low-frequency, high-amplitude artifact noise, which obscure lesion boundaries and reduce diagnostic reliability. To address this issue within the USCT geometry, we propose a modified imaging condition based on implicit full-wavefield decomposition using the Hilbert transform. This approach separates the forward and adjoint wavefields into upgoing/downgoing and leftgoing/rightgoing components, while avoiding the need to explicitly store these large datasets. As a result, it enables effective computation, improves imaging quality, and enhances signal-to-noise ratio. Synthetic experiments with breast and brain models demonstrate the potential applicability of this method for high-resolution USCT.
Zhang et al. (Sun,) studied this question.