WCSE 2016
ISBN: 978-981-11-0008-6 DOI: 10.18178/wcse.2016.06.082

Scattering Correction Based on Regularization De-Convolution for Cone-Beam CT

Rui-Ju Yan, Shi-Peng Xie

Abstract— In Cone-Beam CT (CBCT) imaging systems, the scattering phenomenon has a significant impact on the reconstructed image and is a long-lasting research topic on CBCT. In this paper, we propose a simple, novel and fast approach for mitigating scatter artifacts and increasing the image contrast in CBCT, belonging to the category of convolution-based method in which the projected data is de-convolved with a convolution kernel. A key step in this method is how to determine the convolution kernel. Compared with existing methods, the estimation of convolution kernel is based on bi-l1-l2-norm regularization imposed on both the intermediate the known scatter contaminated projection images g and the convolution kernel. Our approach can reduce the scatter artifacts from 12.930 to 2.133.

Index Terms— scatter correction, cone-beam CT (CBCT), convolution kernel, regularization.

Rui-Ju Yan, Shi-Peng Xie
College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, CHINA


Cite: Rui-Ju Yan, Shi-Peng Xie, "Scattering Correction Based on Regularization De-Convolution for Cone-Beam CT," Proceedings of 2016 6th International Workshop on Computer Science and Engineering, pp. 489-492, Tokyo, 17-19 June, 2016.