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A Novel Tomographic Reconstruction Method Based on the Robust Student's t Function For Suppressing Data Outliers

Kazantsev, D; Bleichrodt, F; Van Leeuwen, T; Kaestner, A; Withers, PJ; Batenburg, KJ; Lee, PD; (2017) A Novel Tomographic Reconstruction Method Based on the Robust Student's t Function For Suppressing Data Outliers. IEEE Transactions on Computational Imaging , 3 (4) pp. 682-693. 10.1109/TCI.2017.2694607. Green open access

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Abstract

Regularized iterative reconstruction methods in computed tomography can be effective when reconstructing from mildly inaccurate undersampled measurements. These approaches will fail, however, when more prominent data errors, or outliers, are present. These outliers are associated with various inaccuracies of the acquisition process: defective pixels or miscalibrated camera sensors, scattering, missing angles, etc. To account for such large outliers, robust data misfit functions, such as the generalized Huber function, have been applied successfully in the past. In conjunction with regularization techniques, these methods can overcome problems with both limited data and outliers. This paper proposes a novel reconstruction approach using a robust data fitting term which is based on the Student's t distribution. This misfit promises to be even more robust than the Huber misfit as it assigns a smaller penalty to large outliers. We include the total variation regularization term and automatic estimation of a scaling parameter that appears in the Student's t function. We demonstrate the effectiveness of the technique by using a realistic synthetic phantom and also apply it to a real neutron dataset.

Type: Article
Title: A Novel Tomographic Reconstruction Method Based on the Robust Student's t Function For Suppressing Data Outliers
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/TCI.2017.2694607
Publisher version: https://doi.org/10.1109/TCI.2017.2694607
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Limited angle regularization, neutron tomography, proximal point, ring artifacts, robust statistics, X-ray CT, zingers
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Mechanical Engineering
URI: https://discovery.ucl.ac.uk/id/eprint/10096684
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