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Evaluation of Rigid and Non-rigid Motion Compensation of Cardiac Perfusion MRI

  • Hui Xue
  • Jens Guehring
  • Latha Srinivasan
  • Sven Zuehlsdorff
  • Kinda Saddi
  • Christophe Chefdhotel
  • Joseph V. Hajnal
  • Daniel Rueckert
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5242)

Abstract

Although the evaluation of cardiac perfusion using MRI could be of crucial importance for the diagnosis of ischemic heart diseases, it is still not a routinely used technique. The major difficulty is that MR perfusion images are often corrupted by inconsistent myocardial motion. Although motion compensation methods have been studied throughout the past decade, no clinically accepted solution has emerged. This is partly due to the lack of comprehensive validation. To address this deficit we collected a large multi-centre MR perfusion dataset and used this to characterize typical myocardial motion and confirmed that under clinically relevant conditions motion correction is a frequent requirement (67% of all 586 cases). We then developed a proposed solution which includes both rigid/affine and the non-rigid image registration. Quantitative validation has been conducted using 6 different statistics to provide a comprehensive evaluation, showing the proposed techniques to be highly robust to different myocardial anatomy and motion patterns as well as to MR imaging acquisition parameters.

Keywords

Motion Compensation Significant Motion Slice Position Myocardium Motion Motion Compensation Algorithm 
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.

Supplementary material

978-3-540-85990-1_5_MOESM1_ESM.zip (5.2 mb)
Electronic Supplementary Material (5,286 KB)

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Hui Xue
    • 1
    • 2
    • 3
  • Jens Guehring
    • 1
  • Latha Srinivasan
    • 2
  • Sven Zuehlsdorff
    • 4
  • Kinda Saddi
    • 1
  • Christophe Chefdhotel
    • 1
  • Joseph V. Hajnal
    • 2
  • Daniel Rueckert
    • 3
  1. 1.Imaging and VisualizationSiemens Corporate ResearchPrincetonUSA
  2. 2.Imaging Sciences DepartmentImperial CollegeLondonUK
  3. 3.Department of ComputingImperial CollegeLondonUK
  4. 4.MR Research and DevelopmentSiemens Medical Solutions USA, Inc.ChicagoUSA

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