A new in-line X-ray phase-contrast computed tomography reconstruction algorithm based on adaptive-weighted...

Area of Science:

• Medical Imaging
• Computational Imaging
• Biomedical Engineering

Background:

• In-line X-ray phase-contrast computed tomography (IL-PCCT) excels at imaging soft tissues but suffers from long scan times and high radiation doses.
• High radiation doses limit the clinical and biomedical applications of IL-PCCT.
• Reducing projection views in IL-PCCT is crucial for dose reduction but can degrade image quality.

Purpose of the Study:

• To develop a novel iterative CT reconstruction algorithm for IL-PCCT.
• To reduce radiation dose by minimizing projection views while preserving image quality.
• To enhance the clinical applicability of IL-PCCT in biomedical imaging.

Main Methods:

• An iterative CT reconstruction algorithm combining Projection Onto Convex Sets (POCS) with adaptive-weighted anisotropic total p-variation (AwaTpV) regularization.
• AwaTpV regularization incorporates horizontal, vertical, and diagonal image gradients for directional continuity.
• Algorithm evaluated using numerical phantoms and synchrotron IL-PCCT data.

Main Results:

• The proposed algorithm effectively reduced artifacts caused by insufficient projection data.
• High-quality image reconstruction was achieved under both noise-free and noisy conditions.
• Edge details in the reconstructed images were well-preserved.
• Significant reduction in radiation dose was demonstrated.

Conclusions:

• The developed iterative algorithm offers an effective approach to decrease radiation dose in IL-PCCT.
• This method enables high-quality imaging with fewer projections, facilitating wider clinical adoption.
• The algorithm shows promise for safer and more efficient biomedical imaging applications.