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    This study introduces a new tomographic method to reduce noise in microstructure characterization. By shifting the object, it separates noise from the actual structure, improving imaging quality.

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    Area of Science:

    • Optics
    • Materials Science
    • Image Processing

    Background:

    • Coherent noise in phase data creates artifacts in tomographic reconstructions, particularly circular structures at the center.
    • Accurate characterization of microstructures is crucial in various scientific and engineering fields.

    Purpose of the Study:

    • To develop a novel tomographic measurement approach for noise-suppressed microstructure characterization.
    • To mitigate the impact of coherent noise artifacts in phase data during tomographic reconstruction.

    Main Methods:

    • An unconventional tomographic measurement configuration is employed, involving deliberate object shifting relative to the rotation axis.
    • This shift spatially separates the reconstructed sample structure from regions of high refractive index perturbations (noise).
    • An automatic focus correction algorithm is used to numerically correct phase data defocusing introduced by the measurement modification.

    Main Results:

    • The proposed method significantly decreases the noise level in tomographic reconstructions.
    • Simulations and experimental measurements of an optical microtip validate the effectiveness of the noise reduction technique.
    • The spatial separation strategy successfully isolates the true microstructure from noise-induced artifacts.

    Conclusions:

    • The novel tomographic measurement approach effectively suppresses noise for enhanced microstructure characterization.
    • This method offers a practical solution for improving the quality of tomographic imaging in microscopy.
    • The validated technique has potential applications in materials science and nanotechnology for detailed structural analysis.