X-ray cone-beam (CB) projection data often contain high amounts of scattered radiation, which must be properly modeled in order to produce accurate computed tomography (CT) reconstructions. A well known correction technique is the scatter kernel superposition (SKS) method that involves deconvolving projection data with kernels derived from pencil beam-generated scatter point-spread functions. The method has the advantages of being practical and computationally efficient but can suffer from inaccuracies. We show that the accuracy of the SKS algorithm can be significantly improved by replacing the symmetric kernels that traditionally have been used with nonstationary asymmetric kernels. We also show these kernels can be well approximated by combinations of stationary kernels thus allowing for efficient implementation of convolution via FFT. To test the new algorithm, Monte Carlo simulations and phantom experiments were performed using a table-top system with geometry and components matching those of the Varian On-Board Imager (OBI). The results show that asymmetric kernels produced substantially improved scatter estimates. For large objects with scatter-to-primary ratios up to 2.0, scatter profiles were estimated to within 10% of measured values. With all corrections applied, including beam hardening and lag, the resulting accuracies of the CBCT reconstructions were within ±25 Hounsfield Units (±2.5%).

Date Published: 12 March 2009
PDF: 12 pages
Proc. SPIE 7258, Medical Imaging 2009: Physics of Medical Imaging, 72581Z (12 March 2009); doi: 10.1117/12.811578

Published in SPIE Proceedings Vol. 7258:
Medical Imaging 2009: Physics of Medical Imaging
Ehsan Samei; Jiang Hsieh, Editor(s)