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Motion Aware MR Imaging via Spatial Core Correspondence

  • Christoph Jud
  • Damien Nguyen
  • Robin Sandkühler
  • Alina Giger
  • Oliver Bieri
  • Philippe C. Cattin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11070)

Abstract

Motion awareness in MR imaging is essential when it comes to long acquisition times. For volumetric high-resolution or temporal resolved images, sporadic subject movements or respiration induced organ motion has to be considered in order to reduce motion artifacts. We present a novel MR imaging sequence and an associated retrospective reconstruction method incorporating motion via spatial correspondence of the k-space center. The sequence alternatingly samples k-space patches located in the center and in peripheral higher frequency regions. Each patch is transformed into the spatial domain in order to normalize for spatial transformations rigidly as well as non-rigidly. The k-space is reconstructed from the spatially aligned patches where the alignment is derived using image registration of the center patches. Our proposed method assumes neither periodic motion nor requires any binning of motion states to properly compensate for movements during acquisition. As we directly acquire volumes, 2D slice stacking is avoided. We tested our method for brain imaging with sporadic head motion and for chest imaging where a volunteer has been scanned under free breathing. In both cases, we demonstrate high-quality 3D reconstructions.

Keywords

Magnetic Resonance Imaging Motion correction 4DMRI 

References

  1. 1.
    Batchelor, P., Atkinson, D., Irarrazaval, P., Hill, D., Hajnal, J., Larkman, D.: Matrix description of general motion correction applied to multishot images. Magn. Reson. Med. 54(5), 1273–1280 (2005)CrossRefGoogle Scholar
  2. 2.
    Haase, A., Frahm, J., Matthaei, D., Hanicke, W., Merboldt, K.D.: Flash imaging. rapid NMR imaging using low flip-angle pulses. J. Magn. Reson. 67(2), 258–266 (1986)Google Scholar
  3. 3.
    Liu, J., Saloner, D.: Accelerated MRI with CIRcular Cartesian UnderSampling (CIRCUS): a variable density cartesian sampling strategy for compressed sensing and parallel imaging. Quant. Imaging Med. Surg. 4(1), 57 (2014)Google Scholar
  4. 4.
    Luo, J., et al.: Nonrigid motion correction with 3D image-based navigators for coronary mr angiography. Magn. Reson. Med. 77(5), 1884–1893 (2017)CrossRefGoogle Scholar
  5. 5.
    Maclaren, J., Herbst, M., Speck, O., Zaitsev, M.: Prospective motion correction in brain imaging: a review. Magn. Reson. Med. 69(3), 621–636 (2013)CrossRefGoogle Scholar
  6. 6.
    Mattes, D., Haynor, D.R., Vesselle, H., Lewellen, T.K., Eubank, W.: PET-CT image registration in the chest using free-form deformations. IEEE Trans. Med. Imaging 22(1), 120–128 (2003)CrossRefGoogle Scholar
  7. 7.
    Pipe, J.G., et al.: Motion correction with PROPELLER MRI: application to head motion and free-breathing cardiac imaging. Magn. Reson. Med. 42(5), 963–969 (1999)CrossRefGoogle Scholar
  8. 8.
    Roemer, P.B., Edelstein, W.A., Hayes, C.E., Souza, S.P., Mueller, O.: The NMR phased array. Magn. Reson. Med. 16(2), 192–225 (1990)CrossRefGoogle Scholar
  9. 9.
    Sandkühler, R., Jud, C., Pezold, S., Cattin, P.C.: Adaptive graph diffusion regularisation for discontinuity preserving image registration. In: Klein, S., Staring, M., Durrleman, S., Sommer, S. (eds.) WBIR 2018. LNCS, vol. 10883, pp. 24–34. Springer, Cham (2018).  https://doi.org/10.1007/978-3-319-92258-4_3CrossRefGoogle Scholar
  10. 10.
    Schmidt, J.F., Buehrer, M., Boesiger, P., Kozerke, S.: Nonrigid retrospective respiratory motion correction in whole-heart coronary MRA. Magn. Reson. Med. 66(6), 1541–1549 (2011)CrossRefGoogle Scholar
  11. 11.
    von Siebenthal, M., Szekely, G., Gamper, U., Boesiger, P., Lomax, A., Cattin, P.: 4D MR imaging of respiratory organ motion and its variability. Phys. Med. Biol. 52(6), 1547 (2007)CrossRefGoogle Scholar
  12. 12.
    White, N., et al.: Promo: Real-time prospective motion correction in MRI using image-based tracking. Magn. Reson. Med. 63(1), 91–105 (2010)MathSciNetCrossRefGoogle Scholar
  13. 13.
    Zaitsev, M., Maclaren, J., Herbst, M.: Motion artifacts in MRI: a complex problem with many partial solutions. J. Magn. Reson. Imaging 42(4), 887–901 (2015)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Christoph Jud
    • 1
  • Damien Nguyen
    • 1
    • 2
  • Robin Sandkühler
    • 1
  • Alina Giger
    • 1
  • Oliver Bieri
    • 1
    • 2
  • Philippe C. Cattin
    • 1
  1. 1.Department of Biomedical EngineeringUniversity of BaselAllschwilSwitzerland
  2. 2.Department of Radiology, Division of Radiological PhysicsUniversity Hospital BaselBaselSwitzerland

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