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Reconstruction of 3D Cardiac MR Images from 2D Slices Using Directional Total Variation

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Molecular Imaging, Reconstruction and Analysis of Moving Body Organs, and Stroke Imaging and Treatment (RAMBO 2017, CMMI 2017, SWITCH 2017)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10555))

Abstract

Cardiac MRI allows for the acquisition of high resolution images of the heart. Long acquisition times of MRI make it impractical to image the full heart in 3D at high resolution. As a result, multiple 2D images are commonly acquired with a slice thickness greater than the in-plane resolution. One way of achieving isotropic high-resolution images is to apply post-processing techniques such as super-resolution to produce high resolution images from low resolution input. We use short-axis stacks as well as orthogonal long-axis views in a super-resolution framework, constraining the reconstruction using the contrast independent directional total variation algorithm to produce a high resolution 3D reconstruction with isotropic resolution. The 3D reconstruction retains the contrast of the short-axis stack, but incorporates the edge information from both the short-axis and the long-axis stacks. Results show improved reconstructions, with a segmentation voxel misclassification rate of 3.51% as opposed to 4.27% using linear interpolation.

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Acknowledgments

NMB acknowledges the support of the RCUK Digital Economy Programme grant number EP/G036861/1 (Oxford Centre for Doctoral Training in Healthcare Innovation). This work was supported by the British Heart Foundation (BHF) [grant numbers PG/13/33/30210, RG/13/8/30266, FS/11/50/29038 and NH/13/30238], the Engineering and Physical Sciences Research Council [grant number EP/J013250/1], and the BHF Centre for Research Excellence [grant number RE/13/1/30181. The authors acknowledge a Wellcome Trust Core Award [grant number 090532/Z/09/Z].

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Authors and Affiliations

  1. Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, UK

    Nicolas Basty & Vicente Grau

  2. Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK

    Darryl McClymont, Irvin Teh & Jürgen E. Schneider

  3. Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK

    Irvin Teh & Jürgen E. Schneider

Authors
  1. Nicolas Basty
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  2. Darryl McClymont
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  3. Irvin Teh
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  4. Jürgen E. Schneider
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  5. Vicente Grau
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Corresponding author

Correspondence to Nicolas Basty .

Editor information

Editors and Affiliations

  1. University College London , London, United Kingdom

    M. Jorge Cardoso

  2. McGill University , Montreal, Québec, Canada

    Tal Arbel

  3. Siemens Medical Solutions, Knoxville, Tennessee, USA

    Fei Gao

  4. Imperial College London , London, United Kingdom

    Bernhard Kainz

  5. Biomedical Imaging Group, Rotterdam, The Netherlands

    Theo van Walsum

  6. Technical University Munich , Munich, Germany

    Kuangyu Shi

  7. Visulytix Limited , London, United Kingdom

    Kanwal K. Bhatia

  8. Biomedical Imaging Group, Rotterdam, The Netherlands

    Roman Peter

  9. University College London, London, United Kingdom

    Tom Vercauteren

  10. University of Bern , Bern, Switzerland

    Mauricio Reyes

  11. Harvard Medical School , Boston, Massachusetts, USA

    Adrian Dalca

  12. University Hospital of Bern , Bern, Switzerland

    Roland Wiest

  13. Biomedical Imaging Group, Rotterdam, The Netherlands

    Wiro Niessen

  14. Academic Medical Center , Amsterdam, The Netherlands

    Bart J. Emmer

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Basty, N., McClymont, D., Teh, I., Schneider, J.E., Grau, V. (2017). Reconstruction of 3D Cardiac MR Images from 2D Slices Using Directional Total Variation. In: Cardoso, M., et al. Molecular Imaging, Reconstruction and Analysis of Moving Body Organs, and Stroke Imaging and Treatment. RAMBO CMMI SWITCH 2017 2017 2017. Lecture Notes in Computer Science(), vol 10555. Springer, Cham. https://doi.org/10.1007/978-3-319-67564-0_13

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  • DOI: https://doi.org/10.1007/978-3-319-67564-0_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67563-3

  • Online ISBN: 978-3-319-67564-0

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