Multispectral x-ray CT: multivariate statistical analysis for efficient reconstruction

Publication: Research - peer-reviewArticle in proceedings – Annual report year: 2017

DOI

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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.
Original languageEnglish
Title of host publicationProceedings Volume 10391, Developments in X-Ray Tomography XI
Number of pages11
PublisherSPIE - International Society for Optical Engineering
Publication date2017
DOIs
StatePublished - 2017
EventSPIE Optical Engineering + Applications - San Diego, United States

Conference

ConferenceSPIE Optical Engineering + Applications
CountryUnited States
CitySan Diego
Period06/08/201710/08/2017
SeriesProceedings of SPIE, the International Society for Optical Engineering
Volume1039113
ISSN0277-786X
CitationsWeb of Science® Times Cited: 0
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