A geometric calibration method for a multi-segment static CT based on ordered subsets of sources and detectors

Area of Science:

• Medical Imaging
• Computed Tomography
• Geometric Calibration

Background:

• Multi-segment static computed tomography (MS-staticCT) offers high temporal resolution but has complex geometric parameters.
• Coupled illumination relationships in MS-staticCT pose calibration challenges.

Purpose of the Study:

• To propose an efficient and accurate geometric calibration method for MS-staticCT systems.
• To address the challenges posed by coupled illumination relationships in MS-staticCT.

Main Methods:

• Developed a geometric calibration method based on ordered subsets of sources and detectors.
• Utilized alternate calibration of source and detector subsets until convergence.
• Employed a calibration phantom and minimized average re-projection error (aRPE) for parameter estimation.
• Implemented parallelizable estimation steps for improved computational efficiency.

Main Results:

• Achieved a low average re-projection error (aRPE) of 0.0087 mm in simulations.
• Obtained clear reconstructed images without misalignment in simulations.
• Improved computational efficiency by a factor of 2.20 compared to traditional methods.
• Met the targeted spatial resolution of 2.5 lp·mm⁻¹ in actual MS-staticCT experiments.

Conclusions:

• The proposed ordered subsets geometric calibration method is efficient and accurate for MS-staticCT.
• The method successfully addresses calibration complexities and improves imaging performance.
• Validated through simulations and experimental results, demonstrating its practical applicability.