Enhanced Hemispherical-array Passive Acoustic Mapping utilizing Dual Apodization with Cross-correlation

Abstract

Hemispherical-array passive acoustic mapping (PAM) has been proposed to monitor transcranial ultrasound treatments in real time by enabling three-dimensional (3D) mapping of cavitation activity in the brain. The traditional hemispherical-array PAM is implemented based on delay-and-sum processing, resulting in low resolution and high-level interference due to the low-frequency limit and the interaction between sound sources. Inspired by our previous work, in this study we apply dual apodization with cross-correlation (DAX) technique in hemispherical-array PAM to achieve better image quality with reduced interference artifacts. The proposed algorithm first designs two complementary receive apodizations, and then measures the similarity between two beamformed signals with the cross-correlation coefficient, finally weights the combined signal with the correlation coefficient. The algorithm is tested through numerical simulations, where a 30-cm and 256-element hemispherical array is used to receive the signal from each element (Gaussian-windowed sinusoidal signal at 600 kHz) in three different source configurations without and with noise. The image enhancement is assessed with signal-to-interference ratio (SIR). The obtained results on simulated data indicate that in the noise-free (noisy) case, the proposed algorithm improves the SIR by 12.0 dB (19.5 dB), 14.3 dB (20.4 dB), and 11.8 dB (18.4 dB) in single-, multi-, and random-source configurations. The proposed hemispherical-array PAM algorithm presented in this study has the potential to provide high-quality 3D cavitation image during transcranial ultrasound treatment.