Frequency Compounding Cross-Spectral Matrix Fitting for Passive Cavitation Imaging

High-intensity focused ultrasound (HIFU) can induce cavitation, which requires monitoring for applications such as sonoporation, targeted drug delivery, and histotripsy. Passive acoustic mapping has been proposed as a cavitation monitoring method, but it suffers from limited axial resolution and coherent artifacts, particularly in noninertial cavitation for the latter, leading to potential mislocalization of the cavitation cloud. Previous work introduced the cross-spectral matrix fitting (CMF), a regularized inverse problem approach, to improve axial resolution. Since coherence artifact positions vary with frequency, a common strategy is to mitigate them by summing maps from different frequencies. In this study, rather than summing frequency-specific maps, we propose weighted frequency compounding-CMF (WFC-CMF), which integrates multiple frequencies directly into the inverse problem and applies regularization to the reconstructed solution. To enhance robustness against outliers, we incorporate a Lorentzian M-estimator. Compared to delay-and-sum, WFC-CMF improves the Dice score by up to 35 points and outperforms summed-frequency CMF (sCMF) up to 14 points.