A Novel Method of Cone Beam CT Projection Binning Based on Image Registration

Area of Science:

• Medical Imaging
• Image Reconstruction
• Computational Imaging

Background:

• Motion artifacts degrade 4D cone beam computed tomography (4D CBCT) image quality.
• Accurate sorting of beam projections is crucial for motion artifact reduction in 4D CBCT.
• Existing projection binning methods have limitations in accuracy and handling irregular respiratory motion.

Purpose of the Study:

• To introduce and evaluate a novel marker-less projection binning method for 4D CBCT.
• To assess the performance of the proposed Image Registration-based Projection Binning (IRPB) method against established techniques.
• To improve the quality of reconstructed 4D CBCT images by minimizing motion-induced artifacts.

Main Methods:

• Developed Image Registration-based Projection Binning (IRPB), a marker-less method for 4D CBCT.
• IRPB utilizes intensity-based feature point detection and trajectory tracking with random sample consensus.
• Evaluated IRPB against Amsterdam Shroud (AS), Fourier Transform (FT), and Local Intensity Feature Tracking (LIFT) methods using phantom and patient datasets.

Main Results:

• IRPB demonstrated superior accuracy in phase shift detection compared to FT and LIFT.
• IRPB achieved significantly higher Peak Signal-to-Noise Ratio (PSNR) values (5.08 dB over AS, 1.05 dB over FT, 2.90 dB over LIFT).
• IRPB resulted in higher Structure SIMilarity Index (SSIM) values (0.87) compared to AS (0.74), FT (0.84), and LIFT (0.70).

Conclusions:

• IRPB is an effective marker-less method for projection binning in 4D CBCT.
• The proposed IRPB method significantly reduces motion artifacts and enhances 4D CBCT image quality.
• IRPB shows superior performance compared to AS, FT, and LIFT methods, particularly for regular and irregular respiratory motion.