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MARS-MD: Rejection based image domain material decomposition

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  • Additional Information
    • Publication Information:
      IOP Publishing Ltd on behalf of Sissa Medialab
    • Publication Date:
      2018
    • Collection:
      Lincoln University (New Zealand): Lincoln U Research Archive
    • Abstract:
      This paper outlines image domain material decomposition algorithms that have been routinely used in MARS spectral CT systems. These algorithms (known collectively as MARS-MD) are based on a pragmatic heuristic for solving the under-determined problem where there are more materials than energy bins. This heuristic contains three parts: (1) splitting the problem into a number of possible sub-problems, each containing fewer materials; (2) solving each sub-problem; and (3) applying rejection criteria to eliminate all but one sub-problem's solution. An advantage of this process is that different constraints can be applied to each sub-problem if necessary. In addition, the result of this process is that solutions will be sparse in the material domain, which reduces crossover of signal between material images. Two algorithms based on this process are presented: the Segmentation variant, which uses segmented material classes to define each sub-problem; and the Angular Rejection variant, which defines the rejection criteria using the angle between reconstructed attenuation vectors.
    • File Description:
      16 pages
    • ISSN:
      1748-0221
    • Relation:
      The original publication is available from IOP Publishing Ltd on behalf of Sissa Medialab - https://doi.org/10.1088/1748-0221/13/05/P05020 - http://dx.doi.org/10.1088/1748-0221/13/05/p05020; Journal of Instrumentation; https://doi.org/10.1088/1748-0221/13/05/P05020; https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=elements_prod&SrcAuth=WosAPI&KeyUT=WOS:000432393900005&DestLinkType=FullRecord&DestApp=WOS_CPL; Bateman et al. (2018). MARS-MD: Rejection based image domain material decomposition. Journal of Instrumentation, 13(5), P05020. doi:10.1088/1748-0221/13/05/P05020; GG0UC (isidoc); https://hdl.handle.net/10182/10189
    • Accession Number:
      10.1088/1748-0221/13/05/P05020
    • Online Access:
      https://doi.org/10.1088/1748-0221/13/05/P05020
      https://hdl.handle.net/10182/10189
      https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=elements_prod&SrcAuth=WosAPI&KeyUT=WOS:000432393900005&DestLinkType=FullRecord&DestApp=WOS_CPL
    • Rights:
      © 2018 CERN. Published by IOP Publishing Ltd on behalf of Sissa Medialab. Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI ; Attribution ; https://creativecommons.org/licenses/by/4.0/
    • Accession Number:
      edsbas.A6185399