Affiliations: [a] Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China
| [b] School of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing, China
| [c] Department of Electrical and Computer Engineering, University of Massachusetts Lowell, Lowell, MA, USA
| [d] College of Mathematics and Statistics, Chongqing University, Chongqing, China
| [e] Engineering Research Center of Industrial Computed Tomography Nondestructive Testing of the Education Ministry of China, Chongqing University, Chongqing, China
| [f] Biomedical Imaging Center, AI-based X-ray Imaging System (AXIS) Lab, Rensselaer Polytechnic Institute, Troy, NY, USA
Abstract: Computed tomography (CT) has been widely applied in medical diagnosis, nondestructive evaluation, homeland security, and other science and engineering applications. Image reconstruction is one of the core CT imaging technologies. In this review paper, we systematically reviewed the currently publicly available CT image reconstruction open source toolkits in the aspects of their environments, object models, imaging geometries, and algorithms. In addition to analytic and iterative algorithms, deep learning reconstruction networks and open codes are also reviewed as the third category of reconstruction algorithms. This systematic summary of the publicly available software platforms will help facilitate CT research and development.
Keywords: CT, image reconstruction, open source, toolkits, algorithm, analytic, iterative, deep learning
