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Quantitative phase microscopy: automated background leveling techniques and smart temporal phase unwrapping.

Goldie Goldstein, Katherine Creath

    Applied Optics
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    This study introduces automated background leveling and smart temporal unwrapping to improve time-dynamic quantitative phase microscopy. These methods create stable phase data, enabling accurate biological analysis from microscopy images.

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    Area of Science:

    • Quantitative Phase Microscopy
    • Biomedical Imaging
    • Optical Microscopy

    Background:

    • Time-dynamic quantitative phase microscopy (QPM) generates raw phase measurements requiring processing for scientific interpretation.
    • Accurate analysis of biological samples using QPM necessitates consistent phase unwrapping and minimal background noise.

    Purpose of the Study:

    • To develop robust methods for processing raw phase data from time-dynamic QPM.
    • To ensure phase measurements are consistently unwrapped and background-free over time.
    • To enable biologically meaningful conclusions from QPM data by stabilizing phase values.

    Main Methods:

    • An automated background leveling procedure was developed to remove background shape and minimize phase fluctuations.
    • A novel method, 'smart temporal unwrapping,' was introduced to address residual differences between sequential frames and ensure consistent unwrapping.
    • These methods were applied and validated on biological datasets.

    Main Results:

    • The automated background leveling procedure effectively stabilized background phase values over time.
    • Smart temporal unwrapping successfully accounted for minor frame-to-frame motion and ensured consistent phase unwrapping.
    • The combined methods significantly minimized processing errors, resulting in stable, time-meaningful phase data.

    Conclusions:

    • The developed processing pipeline enhances the reliability of time-dynamic QPM.
    • Stable and accurately processed phase data are crucial for drawing valid biological conclusions from microscopy.
    • This approach offers a robust solution for analyzing dynamic biological processes using QPM.