Affiliations: [a] School of Mathematics, Shandong University, Jinan, Shandong, China | [b] Biomedical Imaging Center, Rensselaer Polytechnic Institute, Troy, NY, USA | [c] Department of Medical Engineering, Shandong Provincial Chest Hospital, Jinan, Shandong, China | [d] School of Mechanical Engineering and Automation, Beijing University of Aeronautics and Astronautics, Beijing, China | [e] Department of Mathematics, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong | [f] Department of Mathematics, The University of Iowa, Iowa City, IA, USA
Correspondence:
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Corresponding author: Jian-Feng Cai, Department of Mathematics, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong. Tel.: +852 3469 2248; Fax: +852 2358 1643; E-mail: jfcai@ust.hk.
Abstract: Reducing radiation dose is an important goal in medical computed tomography (CT), for which interior tomography is an effective approach. There have been interior reconstruction algorithms for monochromatic CT, but in reality, X-ray sources are polychromatic. Using a polychromatic acquisition model and motivated by framelet-based image processing algorithms, in this paper, we propose an interior reconstruction algorithm to obtain an image with spectral information assuming only one scan with a current energy-integrating detector. This algorithm is a new nonlinear iterative method by minimizing a special functional under a polychromatic acquisition model for X-ray CT, where the attenuation coefficients are energy-dependent. Experimental results validate that our algorithm can effectively reduce the beam-hardening artifacts and metal artifacts. It also produces color overlays which are useful in tumor identification and quantification.
