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Related Experiment Video

Updated: Jan 18, 2026

Three-dimensional Optical-resolution Photoacoustic Microscopy
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D-STAR: Diffusion-Based Sparse Tomographic Angular Recovery for Isotropic-Resolution Photoacoustic Imaging.

Di Kong, Haoyu Yang, Yan Luo

    IEEE Transactions on Medical Imaging
    |May 30, 2025
    PubMed
    Summary
    This summary is machine-generated.

    Diffusion-based Sparse Tomographic Angular Recovery (D-STAR) enhances photoacoustic tomography (PAT) by reducing required imaging angles. This novel method maintains high image quality while improving resolution, contrast, and temporal resolution, minimizing laser exposure.

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    Area of Science:

    • Medical Imaging
    • Computational Imaging
    • Biomedical Engineering

    Background:

    • Anisotropy in imaging systems causes directional degradation, reducing image quality and complicating analysis.
    • Multiangle imaging mitigates anisotropy but increases imaging time and excitation dose.

    Purpose of the Study:

    • To introduce Diffusion-based Sparse Tomographic Angular Recovery (D-STAR) for high-resolution Photoacoustic Tomography (PAT).
    • To reduce the number of required angles in PAT while preserving image quality.
    • To optimize the balance between resolution, signal-to-noise ratio (SNR), and laser exposure.

    Main Methods:

    • Trained a diffusion model on a custom 3D PAT dataset.
    • Developed D-STAR to recover sparse tomographic angular data.
    • Validated the method using excised brain and vessel phantoms.

    Main Results:

    • D-STAR achieved high-fidelity images comparable to full tomographic imaging.
    • The method significantly improved resolution and contrast.
    • Outperformed existing approaches in structural recovery and quantitative data extraction.

    Conclusions:

    • D-STAR offers a novel solution to reduce angular sampling in PAT.
    • The approach enhances imaging flexibility, improves temporal resolution, and minimizes laser exposure.
    • Enables high-quality structural and molecular imaging with reduced hardware requirements.