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    We developed a boundary-element method (BEM) acoustic solver to accurately model skull distortions in photoacoustic tomography neuroimaging. This method improves image quality and computational efficiency for clearer functional brain imaging.

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    Area of Science:

    • Biomedical imaging
    • Acoustic modeling
    • Neuroscience

    Background:

    • Photoacoustic tomography (PAT) offers advanced neuroimaging capabilities, rivaling functional magnetic resonance imaging (fMRI) with enhanced contrast, portability, and cost-effectiveness.
    • A significant hurdle in PAT neuroimaging is correcting skull-induced acoustic distortions, which are critical for accurately detecting subtle functional changes.
    • Existing methods struggle with the computational demands of modeling these distortions, especially for high-accuracy functional imaging.

    Purpose of the Study:

    • To develop and validate a novel acoustic solver using the boundary-element method (BEM) for modeling skull effects in photoacoustic tomography.
    • To demonstrate the efficacy of BEM in de-aberrating PAT images, overcoming limitations of current computational approaches.
    • To establish BEM as a superior technique for skull distortion correction in neuroimaging applications.

    Main Methods:

    • Developed an acoustic solver utilizing the boundary-element method (BEM) to accurately model the acoustic properties of the human skull.
    • Employed boundary meshes and computational compression for enhanced efficiency in the BEM solver.
    • Compared the performance of BEM against the pseudo-spectral time-domain method (PSTD) using ex-vivo human skull imaging data.

    Main Results:

    • The BEM-based solver demonstrated superior computational efficiency and scalability compared to volumetric discretization methods like PSTD.
    • BEM achieved higher accuracy in de-aberrating photoacoustic images affected by skull distortions, outperforming PSTD across multiple performance metrics.
    • Imaging experiments through an ex-vivo adult human skull confirmed the practical advantages of the BEM approach.

    Conclusions:

    • The boundary-element method (BEM) is a highly accurate and computationally efficient technique for modeling skull distortions in photoacoustic tomography.
    • BEM provides a robust solution for de-aberration, significantly enhancing image quality for neuroimaging applications.
    • This work establishes BEM as a valuable tool for photoacoustic tomography and paves the way for advanced BEM-based imaging techniques.