Globally convergent algorithms for maximum a posteriori transmission tomography
IEEE Transactions on Image Processing
Hi-index | 0.00 |
A beam-hardening effect is a common problem affecting the quantitative ability of X-ray computed tomography. We develop a statistical reconstruction for a poly-energetic model, which can effectively reduce beam-hardening effects. A phantom test is used to evaluate our approach in comparison with traditional correction methods. Unlike previous methods, our algorithm utilizes multiple energy-corresponding blank scans to estimate attenuation map for a particular energy spectrum. Therefore, our algorithm has an energy-selective reconstruction. In addition to the benefits of other iterative reconstructions, our algorithm has the advantage in no requirement for prior knowledge about object material, energy spectrum of source and energy sensitivity of the detector. The results showed an improvement in the coefficient of variation, uniformity and signal-to-noise ratio demonstrating better beam hardening correction in our approach.