Exact fan-beam image reconstruction algorithm for truncated projection data acquired from an asymmetric half-size...

Area of Science:

• Medical Imaging
• Computed Tomography (CT)

Background:

• Fan-beam CT imaging often faces data truncation issues with limited detector coverage.
• Asymmetric detector configurations in fan-beam CT lead to truncated projection data at all angles.
• Truncated data significantly degrades image quality in conventional reconstruction algorithms like filtered backprojection (FBP).

Purpose of the Study:

• To introduce and validate a novel algorithm for fan-beam CT image reconstruction that robustly handles data truncation.
• To demonstrate the algorithm's capability to reconstruct images from asymmetrically truncated projection data without explicit rebinning.

Main Methods:

• The study utilizes a fan-beam CT scanning configuration with an asymmetrically positioned, half-sized detector.
• A specific reconstruction algorithm, filtering a backprojection image of differentiated projection data (FBPD), is applied.
• Numerical simulations are performed to verify the algorithm's effectiveness.

Main Results:

• The FBPD algorithm successfully reconstructs the entire image object using truncated data from a full scan (2pi angular range).
• Accurate reconstruction of a region of interest (ROI) is achieved using truncated data from a short-scan mode (less than 2pi).
• The proposed method avoids the need for a data rebinning pre-processing step.

Conclusions:

• The FBPD algorithm offers an effective solution for fan-beam CT data truncation caused by asymmetric detector configurations.
• This approach enables accurate image reconstruction from incomplete projection data, simplifying the reconstruction pipeline by eliminating rebinning.
• The findings are validated through numerical simulations, supporting the algorithm's practical applicability.