UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Model-based iterative reconstruction using higher-order regularization of dynamic synchrotron data

Kazantsev, D; Guo, E; Phillion, AB; Withers, PJ; Lee, PD; (2017) Model-based iterative reconstruction using higher-order regularization of dynamic synchrotron data. Measurement Science and Technology , 28 (9) , Article 094004. 10.1088/1361-6501/aa7fa8. Green open access

[thumbnail of J254_Kazantsev_Meas_Sci_Tech_2017_as_accepted.pdf]
Preview
Text
J254_Kazantsev_Meas_Sci_Tech_2017_as_accepted.pdf - Accepted version

Download (2MB) | Preview

Abstract

We present a novel iterative reconstruction method applied to in situ x-ray synchrotron tomographic data of dendrite formation during the solidification of magnesium alloy. Frequently, fast dynamic imaging projection data are undersampled, noisy, of poor contrast and can contain various acquisition artifacts. Direct reconstruction methods are not suitable and iterative reconstruction techniques must be adapted to the existing data features. Normally, an accurate modelling of the objective function can guarantee a better reconstruction. In this work, we design a special cost function where the data fidelity term is based on the Group-Huber functional to minimize ring artifacts and the regularization term is a higher-order variational penalty. We show that the total variation penalty is unsuitable for some cases and higher-order regularization functionals can ensure a better fit to the expected properties of the data. Additionally, we highlight the importance of 3D regularization over 2D for the problematic data. The proposed method shows a promising performance dealing with angular undersampled noisy dynamic data with ring artifacts.

Type: Article
Title: Model-based iterative reconstruction using higher-order regularization of dynamic synchrotron data
Open access status: An open access version is available from UCL Discovery
DOI: 10.1088/1361-6501/aa7fa8
Publisher version: https://doi.org/10.1088/1361-6501/aa7fa8
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.
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/10049192
Downloads since deposit
57Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item