| Autor: |
Riis, Nicolai André Brogaard, Dong, Yiqiu |
| Přispěvatelé: |
Lellmann, Jan, Modersitzki, Jan, Burger, Martin |
| Jazyk: |
angličtina |
| Rok vydání: |
2019 |
| Předmět: |
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| Zdroj: |
Riis, N A B & Dong, Y 2019, A New Iterative Method for CT Reconstruction with Uncertain View Angles . in J Lellmann, J Modersitzki & M Burger (eds), Proceedings of 7th International Conference on Scale Space and Variational Methods in Computer Vision . Springer, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11603 LNCS, pp. 156-167, 7th International Conference on Scale Space and Variational Methods in Computer Vision, Hofgeismar, Germany, 30/06/2019 . https://doi.org/10.1007/978-3-030-22368-7_13 |
| DOI: |
10.1007/978-3-030-22368-7_13 |
| Popis: |
In this paper, we propose a new iterative algorithm for Computed Tomography (CT) reconstruction when the problem has uncertainty in the view angles. The algorithm models this uncertainty by an additive model-discrepancy term leading to an estimate of the uncertainty in the likelihood function. This means we can combine state-of-the-art regularization priors such as total variation with this likelihood. To achieve a good reconstruction the algorithm alternates between updating the CT image and the uncertainty estimate in the likelihood. In simulated 2D numerical experiments, we show that our method is able to improve the relative reconstruction error and visual quality of the CT image for the uncertain-angle CT problem. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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