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Article type: Research Article
Authors: Trinca, Dragosa; * | Libin, Eduardb
Affiliations: [a] Centre for the Research and Technology of Agro-Environmental and Biological Sciences Vila Real, Portugal | [b] Research Institute of Applied Mathematics and Mechanics Tomsk, Russian Federation
Correspondence: [*] Corresponding author: Dragos Trinca, Centre for the Research and Technology of Agro-Environmental and Biological Sciences Vila Real, Portugal. E-mail: [email protected].
Abstract: Performing X-ray computed tomography (CT) examinations with less radiation has recently received increasing interest: in medical imaging this means less (potentially harmful) radiation for the patient; in non-destructive testing of materials/objects such as testing jet engines, the reduction of the number of projection angles (which for large objects is in general high) leads to a substantial decreasing of the experiment time. In the experiment, less radiation is usually achieved by either (1) reducing the radiation dose used at each projection angle or (2) using sparse view X-ray CT, which means significantly less projection angles are used during the examination. In this work, we study the performance of the recently proposed sinogram-based iterative reconstruction algorithm in sparse view X-ray CT and show that it provides, in some cases, reconstruction accuracy better than that obtained by some of the Total Variation regularization techniques. The provided accuracy is obtained with computation times comparable to other techniques. An important feature of the sinogram-based iterative reconstruction algorithm is that it is simpler and without the many parameters specific to other techniques.
Keywords: Dose reduction, iterative reconstruction, sparse view X-ray CT
DOI: 10.3233/XST-180404
Journal: Journal of X-Ray Science and Technology, vol. 27, no. 1, pp. 37-49, 2019
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