The small animal material discrimination study based on equivalent monochromatic energy projection decomposition method with dual-energy CT system

Article type: Research Article

Authors: Wu, Xiaochuan^a | He, Peng^{a; b; c; *} | Zhang, Yi^d | Chen, Mianyi^a | Wei, Biao^{a; b; c} | Liu, Fenglin^c | An, Kang^c | Feng, Peng^{a; b; c; *}

Affiliations: [a] The Key Lab of Optoelectronic Technology and Systems of the Education Ministry of China, Chongqing University, Chongqing, China | [b] Collaborative Innovation Center for Brain Science, Chongqing University, Chongqing, China | [c] ICT NDT Engineering Research Center, Ministry of Education, Chongqing University, Chongqing, China | [d] College of Computer Science, Sichuan University, Chengdu, China

Correspondence: [*] Corresponding authors: Peng He and Peng Feng. E-mails: [email protected] (P. He) and [email protected] (P. Feng).

Abstract: Material discrimination is an important application of dual-energy computed tomography (CT) techniques. Projection decomposition is a key problem for pre-reconstruction material discrimination. In this study, we focused on the pre-reconstruction space based on the photoelectric and Compton effect decomposition model to characterize different material components, and proposed an efficient method to calculate the projection decomposition coefficient. We converted the complex projection integral into a linear equation by calculating the equivalent monochromatic energy from the high and low energy spectrum. Meanwhile, we constructed a dual-energy CT system based on a photon-counting detector to take small animal scan and material discrimination analysis. Finally, the results of simulation and experimental study demonstrated the feasibility of our proposed new method, and explained the characteristics of photoelectric absorption and Compton scattering reconstruction images.

Keywords: Keywords: Dual-energy CT, photon-counting detector, material discrimination, projection decomposition

DOI: 10.3233/XST-180418

Journal: Journal of X-Ray Science and Technology, vol. 26, no. 6, pp. 919-929, 2018