A tensor PRISM algorithm for multi-energy CT reconstruction and comparative studies.
Different from the single-energy CT (SECT), multi-energy CT (MECT) acquires projection data at different energy spectra, which makes that the MECT has more sparsity among the data of separate energy and over energy. In order to maximize utilization of all these sparse characteristics, this paper proposed a new tensor PRISM model to consistently treat a priori knowledge of the low rank, intensity and sparsity with the higher-dimensional tensor technique. The priori knowledge of low rank corresponds to the stationary background and similarity over the energy, and the intensity and sparsity represents the rest of image features at single energy. Then, the regularization and convex minimization problem was solved by tensor unfolding and an extended tensor-based split-Bregman algorithm. Different from the previous PRISM algorithm, the new algorithm mixed and treated different constraints consistently. Numerical experiments have shown that our tensor PRISM approach performs much better than the popular l1 regularization algorithm in terms of image quality for MECT.
Department of Engineering Physics, Tsinghua University, Beijing, China Key Laboratory of Particle and Radiation Imaging, Ministry of Education, Beijing, China.
Liang
L
Li
Department of Engineering Physics, Tsinghua University, Beijing, China Key Laboratory of Particle and Radiation Imaging, Ministry of Education, Beijing, China.
Zhiqiang
Z
Chen
Biomedical Imaging Cluster, CBIS/BME, Rensselaer Polytechnic Institute, New York, NY, USA.
Ge
G
Wang
Department of Engineering Physics, Tsinghua University, Beijing, China.
Jiyang
J
Chu
Department of Mathematics, University of California, Los Angeles, CA, USA.
Hao
H
Gao
D000465:Algorithms; D003198:Computer Simulation; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D019047:Phantoms, Imaging; D014057:Tomography, X-Ray Computed / Q000379:methods*
Multi-energy CT (MECT); image reconstruction; tensor; tensor PRISM; unfolding