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    Area of Science:

    • Biomedical imaging
    • Optical physics
    • Computational microscopy

    Background:

    • Accurate 3D refractive index (RI) mapping is crucial for understanding biological sample structure and function.
    • Traditional intensity diffraction tomography (IDT) methods often struggle with accurately modeling multiple scattering, especially from high-angle illumination.
    • Existing paraxial approximation models limit the reconstruction quality for complex biological samples.

    Purpose of the Study:

    • To introduce a novel IDT reconstruction algorithm for precise 3D RI distribution recovery of multiple-scattering biological samples.
    • To enhance the accuracy of multiple scattering computation using a split-step non-paraxial (SSNP) model, particularly with high-angle illumination.
    • To develop a computationally efficient and unified reconstruction algorithm applicable to both sequential and multiplexed IDT techniques.

    Main Methods:

    • Development of a split-step non-paraxial (SSNP) model to accurately simulate light scattering.
    • Implementation of a unified reconstruction algorithm leveraging a modular automatic differentiation framework.
    • Application of the algorithm to both sequential and multiplexed IDT modalities for comprehensive data acquisition.

    Main Results:

    • The SSNP model demonstrated superior accuracy in computing multiple scattering compared to paraxial models, especially under high-angle illumination.
    • The unified reconstruction algorithm proved highly computationally efficient.
    • Successful demonstration of the algorithm's capability in reconstructing weakly scattering buccal epithelial cells and strongly scattering live C. elegans.

    Conclusions:

    • The proposed SSNP-based IDT reconstruction algorithm significantly improves the accuracy of 3D RI distribution recovery for biological samples.
    • The developed unified algorithm offers a computationally efficient and versatile tool for advanced optical imaging of diverse biological specimens.
    • This advancement holds potential for enhanced quantitative phase imaging and structural analysis in cell biology and developmental biology research.