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Compressed Sensing Dynamic Reconstruction in 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 7510)

Abstract

This work tackles three-dimensional reconstruction of tomographic acquisitions in C-arm-based rotational angiography. The relatively slow rotation speed of C-arm systems involves motion artifacts that limit the use of three-dimensional imaging in interventional procedures. The main contribution of this paper is a reconstruction algorithm that deals with the temporal variations due to intra-arterial injections. Based on a compressed-sensing approach, we propose a multiple phase reconstruction with spatio-temporal constraints. The algorithm was evaluated by qualitative and quantitative assessment of image quality on both numerical phantom experiments and clinical data from vascular C-arm systems. In this latter case, motion artifacts reduction was obtained in spite of the cone-beam geometry, the short-scan acquisition, and the truncated and subsampled data.

Keywords

Compress Sense Temporal Constraint Static Reconstruction Rotational Angiography Prior Image 
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 2012

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
    • 4
    • 5
  1. 1.Interventional RadiologyGE HealthcareBucFrance
  2. 2.SSE DepartmentSupélecGif-sur-YvetteFrance
  3. 3.Center for Visual ComputingECPChâtenay-MalabryFrance
  4. 4.Center for Visual ComputingENPCChamps-sur-MarneFrance
  5. 5.GALEN TeamINRIA SaclayOrsayFrance

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