Total variation minimization approach in in-line x-ray phase-contrast tomography

Area of Science:

• Medical Imaging
• Computational Physics

Background:

• X-ray Phase-Contrast Tomography (XPCT) reconstruction typically involves solving independent, ill-posed sub-problems.
• Conventional regularization techniques can introduce artifacts into the reconstructed images.

Purpose of the Study:

• To develop and evaluate a novel algebraic reconstruction approach for XPCT.
• To address the limitations of existing methods by solving coupled linear problems.

Main Methods:

• Developed a novel algebraic reconstruction method solving coupled linear problems.
• Utilized an assumption of frequency space band division for tomogram recovery.
• Investigated three algebraic reconstruction algorithms based on Total Variation minimization.

Main Results:

• The proposed algebraic algorithms demonstrated significantly improved accuracy compared to conventional L2-regularized solutions.
• Evaluated performance using both simulated and experimental XPCT data.
• Showcased the effectiveness of algebraic methods in underdetermined systems.

Conclusions:

• Algebraic reconstruction algorithms offer a promising alternative for XPCT.
• This method can enhance accuracy while minimizing acquisition time and radiation dose.
• The findings suggest algebraic algorithms as valuable tools for dose-sensitive imaging applications.