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    Area of Science:

    • Medical Imaging
    • Photon Counting Detectors
    • X-ray Imaging

    Background:

    • K-edge tomographic imaging utilizes photon counting detectors.
    • Energy window width critically impacts signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR).

    Purpose of the Study:

    • To develop an optimization method for determining the optimal energy window width around a K-edge.
    • To enhance SNR and CNR in K-edge tomographic imaging.

    Main Methods:

    • Designed an objective function for projection data SNR based on Poisson distribution.
    • Applied a univariate optimization method to find the optimal X-ray energy window width.

    Main Results:

    • Numerical simulations confirmed the method's effectiveness.
    • The optimal energy window width improved both SNR in projection data and CNR in reconstructed images.

    Conclusions:

    • The proposed method effectively determines optimal energy window width for X-ray photon counting imaging.
    • Achieved optimality in both projection and image domains, improving contrast resolution.