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Motion Quantification and Automated Correction in Clinical RSOM.

Juan Aguirre, Andrei Berezhnoi, Hailong He

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    Raster-scan optoacoustic mesoscopy (RSOM) skin imaging is improved by a new, automated motion correction algorithm. This site-specific approach enhances image quality by compensating for breathing and pulsations, crucial for dermatology applications.

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    Area of Science:

    • Biomedical optics
    • Medical imaging technology
    • Dermatological research

    Background:

    • Raster-scan optoacoustic mesoscopy (RSOM) provides high-resolution, non-invasive skin imaging.
    • RSOM is sensitive to vertical skin motion, impacting diagnostic accuracy.
    • Existing motion correction methods lack full automation and site-specificity.

    Purpose of the Study:

    • To quantify site-specific vertical skin displacements affecting RSOM.
    • To develop a fully automated, site-specific motion correction algorithm for RSOM.
    • To evaluate the algorithm's effectiveness in improving RSOM image quality.

    Main Methods:

    • Quantification of micrometric vertical skin displacements at various body sites.
    • Development of a site-specific, automated motion correction algorithm.
    • Assessment of signal-to-noise ratio improvement in reconstructed RSOM images.

    Main Results:

    • Vertical skin motion magnitude varies significantly by imaging site.
    • Motion is primarily caused by physiological processes like breathing and arterial pulsation.
    • The developed algorithm achieved over a 2-fold improvement in signal-to-noise ratio.

    Conclusions:

    • A novel, automated, site-specific motion correction algorithm significantly enhances RSOM image quality.
    • This algorithm addresses a key limitation of RSOM, enabling broader clinical application.
    • The findings pave the way for realizing the full clinical potential of RSOM in dermatology and beyond.