• DocumentCode
    2052315
  • Title

    PI-Line Based Fan-Beam Lambda Imaging without Singularities

  • Author

    Chen, Lingjian ; Ma, Jianhua ; Chen, Wufan

  • Author_Institution
    Southern Med. Univ., Guangzhou
  • Volume
    4
  • fYear
    2007
  • fDate
    Sept. 16 2007-Oct. 19 2007
  • Abstract
    Since the ionizing radiation may induce cancers and genetic damages in the patient, it is highly desirable to minimize the X-ray dose during a CT scan. As one of the local imaging techniques, the Lambda imaging reduces the X-ray dose and imaging time. But the existence of the singular values results in the low quality of the image. The broad applications of the Pi-lines proof that it can deal with the truncated projections effectively. In this work, we propose a new exact Lambda imaging algorithm based on Wang G´s local imaging method and Pi-lines segment to reconstruct an image with utilizing a Gaussian kernel function convoluting the projection data. We also analyze how to choose the parameters of the Gaussian kernel function. Numerical simulations support our new reconstruction algorithm with high quality reconstruction image.
  • Keywords
    Gaussian processes; cancer; computerised tomography; diagnostic radiography; image reconstruction; image resolution; medical image processing; CT scan; Gaussian kernel function; Pi-lines segment; X-ray dose minimization; cancer diagnosis; fan-beam lambda imaging algorithm; image quality; image reconstruction algorithm; Cancer; Computed tomography; Data analysis; Genetics; Image reconstruction; Image segmentation; Ionizing radiation; Kernel; Optical imaging; X-ray imaging; PI-line; fan-beam; lambda tomography; singularities; truncations;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 2007. ICIP 2007. IEEE International Conference on
  • Conference_Location
    San Antonio, TX
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4244-1437-6
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2007.4379973
  • Filename
    4379973