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Proceedings Paper

Multispectral x-ray CT: multivariate statistical analysis for efficient reconstruction
Author(s): Mina Kheirabadi; Wail Mustafa; Mark Lyksborg; Ulrik Lund Olsen; Anders Bjorholm Dahl
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Paper Abstract

Recent developments in multispectral X-ray detectors allow for an efficient identification of materials based on their chemical composition. This has a range of applications including security inspection, which is our motivation. In this paper, we analyze data from a tomographic setup employing the MultiX detector, that records projection data in 128 energy bins covering the range from 20 to 160 keV. Obtaining all information from this data requires reconstructing 128 tomograms, which is computationally expensive. Instead, we propose to reduce the dimensionality of projection data prior to reconstruction and reconstruct from the reduced data. We analyze three linear methods for dimensionality reduction using a dataset with 37 equally-spaced projection angles. Four bottles with different materials are recorded for which we are able to obtain similar discrimination of their content using a very reduced subset of tomograms compared to the 128 tomograms that would otherwise be needed without dimensionality reduction.

Paper Details

Date Published: 6 October 2017
PDF: 11 pages
Proc. SPIE 10391, Developments in X-Ray Tomography XI, 1039113 (6 October 2017); doi: 10.1117/12.2273338
Show Author Affiliations
Mina Kheirabadi, Technical Univ. of Denmark (Denmark)
Wail Mustafa, Technical Univ. of Denmark (Denmark)
Mark Lyksborg, Technical Univ. of Denmark (Denmark)
Ulrik Lund Olsen, Technical Univ. of Denmark (Denmark)
Anders Bjorholm Dahl, Technical Univ. of Denmark (Denmark)

Published in SPIE Proceedings Vol. 10391:
Developments in X-Ray Tomography XI
Bert Müller; Ge Wang, Editor(s)

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