A New Iterative Method for CT Reconstruction with Uncertain View Angles
Autor: | Yiqiu Dong, Nicolai Andre Brogaard Riis |
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Rok vydání: | 2019 |
Předmět: |
medicine.diagnostic_test
Computer science Iterative method ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Computed tomography 02 engineering and technology 010502 geochemistry & geophysics 01 natural sciences Regularization (mathematics) Uncertainty estimate Prior probability 0202 electrical engineering electronic engineering information engineering medicine Errors-in-variables models 020201 artificial intelligence & image processing Likelihood function Algorithm Ct reconstruction 0105 earth and related environmental sciences |
Zdroj: | Lecture Notes in Computer Science ISBN: 9783030223670 SSVM |
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 |
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