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Updated: Sep 16, 2025

Evanescent Field Based Photoacoustics: Optical Property Evaluation at Surfaces
Published on: July 26, 2016
High-Quality Passive Acoustic Mapping With the Cross-Correlated Angular Spectrum Method
Abstract:
While passive acoustic mapping (PAM) has been advanced for monitoring acoustic cavitation activity in focused ultrasound (FUS) therapy, achieving both real-time and high-quality imaging capabilities is still challenging. The angular spectrum (AS) method presents the most efficient algorithm for PAM, but it suffers from artifacts and low resolution due to the diffraction pattern of the imaging array. Data-adaptive beamformers suppress artifacts well, but their overwhelming computational complexity, more than two orders of magnitude higher than the classical time exposure acoustic (TEA) method, hinders their application in real time. In this work, we introduce the cross-correlated AS method to address the challenge. This method is based on cross-correlating the AS back-propagated wave fields, in the frequency domain (FD), measured by different apodized subapertures of the transducer array to provide the normalized cross-correlation coefficient (NCC) matrix for artifacts suppression. We observed that the spatial pattern of NCC matrix is variable, which can be utilized by the triple apodization with cross correlation (TAX) with AS scheme, namely, the AS-TAX method, for optimal artifacts suppression outcomes. Both the phantom and mouse tumor experiments showed that: 1) the AS-TAX method has comparable image quality as the data-adaptive beamformers, reducing the energy spread area (ESA) by 34.8%-65.0% and improving image signal-to-noise ratio (ISNR) by 10.6-14.4 dB compared to TEA; 2) it reduces the computational complexity by two orders of magnitude compared to TEA allowing millisecond-level image reconstruction speed with a parallel implementation; and 3) it can well map microbubble cavitation activity of different status (stable or inertial). The AS-TAX method represents a real-time approach to monitor cavitation-based FUS therapy with high image quality.
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