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Multigrid reconstruction in tomographic imaging
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Medical Imaging.ORCID iD: 0000-0003-1002-2070
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2019 (English)In: IEEE Transactions on Radiation and Plasma Medical Sciences, ISSN 2469-7311Article in journal (Refereed) Published
Abstract [en]

In this work, we present an efficient methodology for multigrid tomographic image reconstruction from non-truncated projection data. By partitioning the reconstruction domain and adapting the forward and backward operators, an image can be reconstructed accurately within multiple domains of varying discretisation or regularisation. We demonstrate the efficacy of the multigrid reconstruction principle using simulated data for quantitative assessment and experimental measurements from a μ-CT scanner for a clinically relevant use case scenario. A major advantage of using multiple reconstruction grids is the possibility to drastically reduce the number of unknowns in the inverse problem, and thereby the associated computational cost. This cost reduction helps to enlarge the class of available algorithms in applications with strict limitations on computation time or resources, and it enables full system resolution reconstruction of subregions that would otherwise be infeasible for the full field of view. The numerical experiments, along with a brief error analysis, show that the expected artefacts from coarse discretisation outside the region of interest become noticeable only for large differences in discretisation between subregions.

Place, publisher, year, edition, pages
2019.
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Electrical Engineering, Electronic Engineering, Information Engineering
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URN: urn:nbn:se:kth:diva-264038DOI: 10.1109/TRPMS.2019.2942186OAI: oai:DiVA.org:kth-264038DiVA, id: diva2:1371823
Note

QC 20191121

Available from: 2019-11-21 Created: 2019-11-21 Last updated: 2019-11-21Bibliographically approved

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Marlevi, David

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