3D algebraic iterative reconstruction for cone-beam x-ray differential phase-contrast computed tomography

Area of Science:

• Medical Imaging
• Physics
• Computational Science

Background:

• Cone-beam x-ray differential phase-contrast computed tomography (DPC-CT) offers high resolution and contrast in compact systems.
• Existing FDK reconstruction algorithms struggle with cone-beam artifacts at larger angles.
• There is a need for improved reconstruction methods in DPC-CT.

Purpose of the Study:

• To develop and evaluate a novel algebraic iterative reconstruction (AIR) method for cone-beam DPC-CT.
• To address and mitigate cone-beam artifacts inherent in current DPC-CT reconstruction techniques.
• To demonstrate the efficacy of the proposed AIR method compared to FDK.

Main Methods:

• Proposed an algebraic iterative reconstruction (AIR) approach for cone-beam DPC-CT.
• Modeled reconstruction as an optimization problem for discrete object representation.
• Incorporated derivative operations on forward projections to handle differential phase contrast data.
• Utilized an algebraic reconstruction technique for ray-by-ray image reconstruction.

Main Results:

• The proposed AIR method significantly reduces cone-beam artifacts.
• AIR demonstrated superior performance compared to the FDK algorithm under large cone-beam angles.
• Numerical studies and experimental verification confirmed the algorithm's effectiveness.

Conclusions:

• The developed AIR method is a viable and effective solution for cone-beam DPC-CT reconstruction.
• This algorithm offers improved image quality by minimizing artifacts, particularly in challenging large cone-beam scenarios.
• The AIR method holds promise for advancing future cone-beam DPC-CT applications.