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Deformable Image Registration and Intensity Correction of Cardiac Perfusion MRI

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Statistical Atlases and Computational Models of the Heart - Imaging and Modelling Challenges (STACOM 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8896))

Abstract

Dynamic contrast Magnetic Resonance myocardial perfusion imaging has evolved into an accurate technique for the diagnosis of coronary artery disease. In this manuscript, we introduce and evaluate the performance of a non-rigid joint multi-level image registration and intensity correction algorithm on a common dataset. An objective functional is formed for which the corresponding Hessian and Jacobian is computed and employed in a multi-level Gauss-Newton minimization approach. In this paper, our experiments are based on elastic regularization on the transformation and total variation on the intensity correction. Our preliminary validations suggest that the registration scheme provides suitable motion correction if the parameters in the algorithm are properly tuned.

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Author information

Authors and Affiliations

  1. Faculty of Science, University of Ontario Institute of Technology, 2000 Simcoe Street North, Oshawa, ON, L1H 7K4, Canada

    Mehran Ebrahimi & Sancgeetha Kulaseharan

Authors
  1. Mehran Ebrahimi
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  2. Sancgeetha Kulaseharan
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Corresponding author

Correspondence to Mehran Ebrahimi .

Editor information

Editors and Affiliations

  1. University Pompeu Fabra, Barcelona, Spain

    Oscar Camara

  2. Siemens Corporate Technology, Princeton, New Jersey, USA

    Tommaso Mansi

  3. Sunnybrook Research Institute, Toronto, Ontario, Canada

    Mihaela Pop

  4. St. Thomas Hospital, London, United Kingdom

    Kawal Rhode

  5. Inria, Sophia Antipolis, France

    Maxime Sermesant

  6. University of Auckland, Auckland, New Zealand

    Alistair Young

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Ebrahimi, M., Kulaseharan, S. (2015). Deformable Image Registration and Intensity Correction of Cardiac Perfusion MRI. In: Camara, O., Mansi, T., Pop, M., Rhode, K., Sermesant, M., Young, A. (eds) Statistical Atlases and Computational Models of the Heart - Imaging and Modelling Challenges. STACOM 2014. Lecture Notes in Computer Science(), vol 8896. Springer, Cham. https://doi.org/10.1007/978-3-319-14678-2_2

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  • DOI: https://doi.org/10.1007/978-3-319-14678-2_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14677-5

  • Online ISBN: 978-3-319-14678-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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