• DocumentCode
    257832
  • Title

    Coded aperture design in compressive X-ray tomography

  • Author

    Cuadros, Angela P. ; Arce, Gonzalo R. ; Arguello, Henry

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Delaware, Newark, DE, USA
  • fYear
    2014
  • fDate
    3-5 Dec. 2014
  • Firstpage
    656
  • Lastpage
    659
  • Abstract
    Coded aperture X-Ray tomography places a physical coded aperture in front of an X-ray source, the elements in the code either block or let an X-ray beam pass, which produces a patterned compressive projection onto the detector. Given several projections, compressed sensing (CS) reconstruction algorithms are then used to recover the three-dimensional object. The motivation to use coded apertures in this problem, is to reduce the number of measurements (projections) that in this case is equivalent to less radiation exposure to a patient. In this work, we consider the tomosynthesis problem, consisting of multiple X-ray sources which are placed over a three-dimensional data cube. The energy of each of the sources is modulated by a set of coded apertures. The projections are measured by a two-dimensional detector located below the object. Random coded apertures have been used before obtaining promising results. In this paper, the coded apertures are optimized using the generalized mapping of the cone beam energy onto the detector. In our scenario, the PSNR of the reconstructions images by using the optimized codes is up to 3 dB higher than those attained by the random coded apertures.
  • Keywords
    compressed sensing; computerised tomography; image coding; image reconstruction; medical image processing; CS; PSNR; X-ray beam pass; coded aperture X-ray tomography; coded aperture design; compressed sensing reconstruction algorithms; compressive X-ray tomography; cone beam energy; generalized mapping; multiple X-ray sources; optimized codes; patterned compressive projection; physical coded aperture; random coded apertures; three-dimensional data cube; three-dimensional object; tomosynthesis problem; two-dimensional detector; Apertures; Computed tomography; Detectors; Image reconstruction; Optimization; X-ray tomography; coded-apertures; compressed sensing; computed tomography;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal and Information Processing (GlobalSIP), 2014 IEEE Global Conference on
  • Conference_Location
    Atlanta, GA
  • Type

    conf

  • DOI
    10.1109/GlobalSIP.2014.7032199
  • Filename
    7032199