The reconstruction problem has arisen in a large number of scientific fields (including computed tomography, electron microscopy, radiology, radio astronomy and holography). Many different methods (algorithms) have been suggested for its solution. SNARK09 is a programming system for the reconstruction of 2D images from 1D projections. It is designed to help researchers interested in developing and evaluating reconstruction algorithms. In the area of image reconstruction, researchers often desire to compare two or more reconstruction techniques and assess their relative merits. SNARK09 provides a uniform framework in which to implement algorithms and evaluate their performance. SNARK09 has been designed to treat both parallel and divergent projection geometries and can create test data for use by reconstruction algorithms. A number of frequently used reconstruction algorithms are incorporated.

References in zbMATH (referenced in 17 articles )

Showing results 1 to 17 of 17.
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  1. Nikazad, Touraj; Abbasi, Mokhtar; Elfving, Tommy: Error minimizing relaxation strategies in Landweber and Kaczmarz type iterations (2017)
  2. Nikazad, T.; Karimpour, M.: Controlling noise error in block iterative methods (2016)
  3. Herman, Gabor T.: Tomography (2015)
  4. Censor, Yair; Davidi, Ran; Herman, Gabor T.; Schulte, Reinhard W.; Tetruashvili, Luba: Projected subgradient minimization versus superiorization (2014)
  5. Scolnik, H.; Echebest, N.; Guardarucci, M.T.: On the incomplete oblique projections method for solving box constrained least squares problems (2014)
  6. Nikazad, Touraj; Abbasi, Mokhtar: An acceleration scheme for cyclic subgradient projections method (2013)
  7. Censor, Yair; Chen, Wei; Combettes, Patrick L.; Davidi, Ran; Herman, Gabor T.: On the effectiveness of projection methods for convex feasibility problems with linear inequality constraints (2012)
  8. Elfving, Tommy; Hansen, Per Christian; Nikazad, Touraj: Semiconvergence and relaxation parameters for projected SIRT algorithms (2012)
  9. Hansen, Per Christian; Saxild-Hansen, Maria: AIR tools -- a MATLAB package of algebraic iterative reconstruction methods (2012)
  10. Scolnik, H.D.; Echebest, N.E.; Guardarucci, M.T.: Implicit regularization of the incomplete oblique projections method (2009)
  11. Scolnik, H.D.; Echebest, N.E.; Guardarucci, M.T.: Incomplete oblique projections method for solving regularized least-squares problems in image reconstruction (2008)
  12. Scolnik, H.D.; Echebest, N.; Guardarucci, M.T.; Vacchino, M.C.: Incomplete oblique projections for solving large inconsistent linear systems (2008)
  13. Gordon, Dan: Parallel art for image reconstruction in CT using processor arrays (2006)
  14. Santos, Reginaldo J.; De Pierro, Álvaro R.: The effect of the nonlinearity on GCV applied to conjugate gradients in computerized tomography (2006)
  15. Santos, Reginaldo J.: Preconditioning conjugate gradient with symmetric algebraic reconstruction technique (ART) in computerized tomography (2003)
  16. Vardi, Eilat; Herman, Gabor T.; Kong, T.Yung: Speeding up stochastic reconstructions of binary images from limited projection directions (2001)
  17. Stricker, Josef; Censor, Yair; Zakharin, Boris: Inhomogeneous turbulent field diagnostics by distance-dependent tomographic reconstruction techniques (1996)

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