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Compressed Sensing Based 3D Tomographic Reconstruction for Rotational Angiography

  • Hélène Langet
  • Cyril Riddell
  • Yves Trousset
  • Arthur Tenenhaus
  • Elisabeth Lahalle
  • Gilles Fleury
  • Nikos Paragios
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6891)

Abstract

In this paper, we address three-dimensional tomographic reconstruction of rotational angiography acquisitions. In clinical routine, angular subsampling commonly occurs, due to the technical limitations of C-arm systems or possible improper injection. Standard methods such as filtered backprojection yield a reconstruction that is deteriorated by sampling artifacts, which potentially hampers medical interpretation.

Recent developments of compressed sensing have demonstrated that it is possible to significantly improve reconstruction of subsampled datasets by generating sparse approximations through ℓ1-penalized minimization. Based on these results, we present an extension of the iterative filtered backprojection that includes a sparsity constraint called soft background subtraction.

This approach is shown to provide sampling artifact reduction when reconstructing sparse objects, and more interestingly, when reconstructing sparse objects over a non-sparse background. The relevance of our approach is evaluated in cone-beam geometry on real clinical data.

Keywords

Compressed Sensing Sparsity Constraint Positivity Constraint Sparse Approximation Rotational Angiography 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Hélène Langet
    • 1
    • 2
    • 3
  • Cyril Riddell
    • 1
  • Yves Trousset
    • 1
  • Arthur Tenenhaus
    • 2
  • Elisabeth Lahalle
    • 2
  • Gilles Fleury
    • 2
  • Nikos Paragios
    • 3
  1. 1.GE HealthcareBucFrance
  2. 2.Department of Signal Processing and Electronic SystemsSupélecGif-sur-YvetteFrance
  3. 3.Applied Mathematics and Systems DepartmentEcole Centrale ParisChâtenay-MalabryFrance

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