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Approximating Algebraic Tomography Methods by Filtered Backprojection : A Local Filter Approach

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Języki publikacji
EN
Abstrakty
EN
Filtered Backprojection is the most widely used reconstruction method in transmission tomography. The algorithm is computationally efficient, but requires a large number of low-noise projections acquired over the full angular range to produce accurate reconstructions. Algebraic reconstruction methods on the other hand are in general more robust with respect to noise and can incorporate the available angular range in the underlying projection model. A drawback of these methods is their higher computational cost. In a recent article, we demonstrated that for linear algebraic reconstruction methods, a filter can be computed such that applying Filtered Backprojection using this filter yields reconstructions that approximate the algebraic method. In the present work, we explore a modification of this approach, where we use more than one algebraic filter in the reconstructions, each covering a different region of the reconstruction grid. We report the results of a series of experiments to determine the how well the reconstruction and approximation accuracy of this approach.
Wydawca
Rocznik
Strony
1--19
Opis fizyczny
Bibliogr. 16 poz., rys., wykr.
Twórcy
autor
  • Centrum Wiskunde & Informatica, Science Park 123, Amsterdam, The Netherlands
  • Centrum Wiskunde & Informatica, Science Park 123, Amsterdam, The Netherlands
  • iMinds-Vision Lab, University of Antwerp, Belgium
  • Mathematical Institute, Leiden University, The Netherlands
Bibliografia
  • [1] Andersen, A. H., Kak, A. C.: Simultaneous Algebraic Reconstruction Technique (SART): a superior implementation of the ART algorithm, Ultrason. Img., 6, 1984, 81–94.
  • [2] Batenburg, K. J., Plantagie, L.: Fast Approximation of Algebraic Reconstruction Methods for Tomography, IEEE Trans. Im. Proc., 21(8), 2012, 3648–3658.
  • [3] Buzug, T. M.: Computed Tomography: From Photon Statistics to Modern Cone-Beam CT, Springer, 2008.
  • [4] Feldkamp, L. A., Davis, L. C., Kress, J. W.: Practical cone-beam algorithm, J. Opt. Soc. Am., 1(A6), 1984, 612–619.
  • [5] Gilbert, P.: Iterative methods for the three-dimensional reconstruction of an object from projections, Journal of Theoretical Biology, 1972.
  • [6] Gregor, J., Benson, T.: Computational analysis and improvement of SIRT, IEEE Trans. Med. Imaging, 2008.
  • [7] Herman, G. T.: Fundamentals of Computerized Tomography: Image Reconstruction from Projections, 2nd edition, Springer, 2009.
  • [8] Joseph, P. M.: An improved algorithm for reprojecting rays through pixel images, IEEE Trans. Med. Imag., MI-1(3), 1982, 192–196.
  • [9] Kak, A. C., Slaney, M.: Principles of Computerized Tomographic Imaging, SIAM, 2001.
  • [10] Kunze, H., Härer, W., Orman, J., Mertelmeier, T., Stierstorfer, K.: Filter determination for tomosynthesis aided by iterative reconstruction techniques, Proc. of Fully3D, 2007, 309–312.
  • [11] Louis, A. K., Schuster, T.: A Novel Filter Design Technique in 2D - Computerized Tomography, Inverse Problems, 1995.
  • [12] Ludwig, J., Mertelmeier, T., Kunze, H., Härer, W.: A Novel Approach for Filtered Backprojection in Tomosynthesis Based on Filter Kernels Determined by Iterative Reconstruction Techniques, Proc. of IWDM, 2008.
  • [13] Markoe, A.: Analytic Tomography, Cambridge University Press, 2006.
  • [14] Pan, X., Sidky, E. Y., Vannier, M.: Why do commercial CT scanners still employ traditional, filtered backprojection for image reconstruction?, Inv. Problems, 25, 2009, 123009.
  • [15] Shepp, L. A., Logan, B. F.: The Fourier reconstruction of a head section, IEEE Trans. Nucl. Science, 1974.
  • [16] Y. Wei, G. Wang, J. H.: An Intuitive Discussion on the Ideal Ramp Filter in Computed Tomography (I), J. Comput. Math. Appl., 2005.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-b243cf7f-56ba-4f56-beac-d1aeece204a0
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