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    Area of Science:

    • Medical Imaging
    • Radiological Physics
    • Computational Imaging

    Background:

    • Multi-source interior computed tomography (CT) offers fast, low-dose imaging but suffers from X-ray cross-scatter artifacts.
    • Existing hardware-based scatter correction methods require system modifications.
    • Effective scatter correction is crucial for maintaining image quality in advanced CT architectures.

    Purpose of the Study:

    • To develop and validate a novel software-based scatter correction method for multi-source interior CT.
    • To address the limitations of hardware-based approaches by introducing a non-invasive solution.
    • To improve the diagnostic accuracy of multi-source CT by reducing scatter-induced image degradation.

    Main Methods:

    • A physics-based model was analytically derived to calculate forward and cross X-ray scatter signals.
    • The physics model was integrated into an iterative framework for scatter artifact reduction.
    • The method was tested using phantom data from Monte Carlo simulations and physical experiments.

    Main Results:

    • The software-based method significantly reduced scatter artifacts, even with a single iteration.
    • Reconstructed images rapidly converged to scatter-free references within a few iterations.
    • CT number errors in regions of interest decreased to ~46 HU, and contrast-noise-ratio improved by up to 44.3%.

    Conclusions:

    • The proposed physics model-based iterative scatter correction is effective for multi-source CT.
    • This software-only approach offers a practical solution for scatter reduction without hardware modifications.
    • The method shows promise for enhancing image quality in dual-source and multi-source CT systems.