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<p>X-ray computed tomography (CT) is a non-invasive diagnostic technology that has been widely used for various clinical applications. However, CT image quality becomes severely degraded when the X-ray dose is reduced. To reconstruct high-quality low-dose CT image, we present a sub-pixel anisotropic diffusion (SAD) for statistical iterative reconstruction (SIR), based on the penalized weighted least-squares (PWLS) model, termed as PWLS-SAD. Specifically, the SAD uses sub-pixel difference as a generalized form of the first-order derivative, replacing the original first-order derivative in anisotropic diffusion. An alternative minimization algorithm is used to solve the associated objective function. XCAT phantom simulations, anthropomorphic torso phantom measurements, and clinical data were used for the experiment. Experimental results show that PWLS-SAD technique achieves superior performance compared to competing methods, particularly in terms of suppressing image noise, enhancing the visibility of low-contrast structures, and maintaining edge detail.</p>

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Iterative Reconstruction for Low-dose X-ray Computed Tomography Using Sub-pixel Anisotropic Diffusion

  • 期刊论文

  • 发表日期：

    2025年12月28日

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  • Shanzhou Niu,
  • Shizhou Tang,
  • Yuxin Huang,
  • Yi Luo,
  • Tinghua Wang,
  • Hanming Liu,
  • Jing Wang,
  • You Zhang

摘要

X-ray computed tomography (CT) is a non-invasive diagnostic technology that has been widely used for various clinical applications. However, CT image quality becomes severely degraded when the X-ray dose is reduced. To reconstruct high-quality low-dose CT image, we present a sub-pixel anisotropic diffusion (SAD) for statistical iterative reconstruction (SIR), based on the penalized weighted least-squares (PWLS) model, termed as PWLS-SAD. Specifically, the SAD uses sub-pixel difference as a generalized form of the first-order derivative, replacing the original first-order derivative in anisotropic diffusion. An alternative minimization algorithm is used to solve the associated objective function. XCAT phantom simulations, anthropomorphic torso phantom measurements, and clinical data were used for the experiment. Experimental results show that PWLS-SAD technique achieves superior performance compared to competing methods, particularly in terms of suppressing image noise, enhancing the visibility of low-contrast structures, and maintaining edge detail.