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    Image reconstruction for view-limited x-ray CT in baggage scanning

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    Author
    Mandava, Sagar
    Coccarelli, David
    Greenberg, Joel A.
    Gehm, Michael E.
    Ashok, Amit
    Bilgin, Ali
    Affiliation
    Univ Arizona, Dept Elect & Comp Engn
    Univ Arizona, Coll Opt Sci
    Issue Date
    2017-05-01
    Keywords
    Image reconstruction
    security scanning
    view-limited imaging
    
    Metadata
    Show full item record
    Publisher
    SPIE-INT SOC OPTICAL ENGINEERING
    Citation
    Sagar Mandava, David Coccarelli, Joel A. Greenberg, Michael E. Gehm, Amit Ashok, Ali Bilgin, "Image reconstruction for view-limited x-ray CT in baggage scanning", Proc. SPIE 10187, Anomaly Detection and Imaging with X-Rays (ADIX) II, 101870F (1 May 2017); doi: 10.1117/12.2265491; http://dx.doi.org/10.1117/12.2265491
    Journal
    ANOMALY DETECTION AND IMAGING WITH X-RAYS (ADIX) II
    Rights
    © 2017 SPIE.
    Collection Information
    This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
    Abstract
    X-ray CT based baggage scanners are widely used in security applications. Recently, there has been increased interest in view-limited systems which can improve the scanning throughput while maintaining the threat detection performance. However as very few view angles are acquired in these systems, the image reconstruction problem is challenging. Standard reconstruction algorithms such as the filtered backprojection create strong artifacts when working with view-limited data. In this work, we study the performance of a variety of reconstruction algorithms for both single and multi-energy view-limited systems.
    ISSN
    0277-786X
    DOI
    10.1117/12.2265491
    Version
    Final published version
    Sponsors
    U.S. Department of Homeland Security (Department of Homeland Security) [HSHQDC-14-C-BOOIO]; University of Arizona Technology Research Initiative Fund (TRIF) fellowship
    Additional Links
    http://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.2265491
    ae974a485f413a2113503eed53cd6c53
    10.1117/12.2265491
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