Optimization-based design for artifact reduction in advanced diagnostic CT

Dan Xia; Yan Liu; Zhou Yu; Buxin Chen; Richard Thompson; Emil Y. Sidky; Xiaochuan Pan

doi:10.1117/12.2292054

9 March 2018 Optimization-based design for artifact reduction in advanced diagnostic CT

Dan Xia, Yan Liu, Zhou Yu, Buxin Chen, Richard Thompson, Emil Y. Sidky, Xiaochuan Pan

Proceedings Volume 10573, Medical Imaging 2018: Physics of Medical Imaging; 105734A (2018) https://doi.org/10.1117/12.2292054
Event: SPIE Medical Imaging, 2018, Houston, Texas, United States

Abstract

Cone-beam artifact may be observed in the images reconstructed from circular trajectory data by use of the FDK algorithm or its variants for an imaged subject with longitudinally strong contrast variation in advanced diagnostic CT with a large number of detector rows. Existing algorithms have limited success in correcting for the effect of the cone-beam artifacts especially on the reconstruction of low-contrast soft-tissue. In the work, we investigate and develop optimization-based reconstruction algorithms to compensate for the cone-beam artifacts in the reconstruction of low-contrast anatomies. Specifically, we investigate the impact of optimization-based reconstruction design based upon different data-fidelity terms on the artifact correction by using the Chambolle- Pock (CP) algorithm tailored to each of the specific data-fidelity terms considered. We performed numerical studies with real data collected with the 320-slice Canon Medical System CT scanner, demonstrated the effectiveness of the optimization-based reconstruction design, and identified the optimization-based reconstruction that corrects most effectively for the cone-beam artifacts.

Citation Download Citation

Dan Xia, Yan Liu, Zhou Yu, Buxin Chen, Richard Thompson, Emil Y. Sidky, and Xiaochuan Pan "Optimization-based design for artifact reduction in advanced diagnostic CT", Proc. SPIE 10573, Medical Imaging 2018: Physics of Medical Imaging, 105734A (9 March 2018); https://doi.org/10.1117/12.2292054

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