Deformable Mosaicing for Whole-Body MRI

  • Christian Wachinger
  • Ben Glocker
  • Jochen Zeltner
  • Nikos Paragios
  • Nikos Komodakis
  • Michael Sass Hansen
  • Nassir Navab
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5242)


Whole-body magnetic resonance imaging is an emerging application gaining vast clinical interest during the last years. Although recent technological advances shortened the longish acquisition time, this is still the limiting factor avoiding its wide-spread clinical usage. The acquisition of images with large field-of-view helps to relieve this drawback, but leads to significantly distorted images. Therefore, we propose a deformable mosaicing approach, based on the simultaneous registration to linear weighted averages, to correct for distortions in the overlapping area. This method produces good results on in-vivo data and has the advantage that a seamless integration into the clinical workflow is possible.


Dynamic Time Warping Normalize Cross Correlation Deformable Image Registration Deformation Grid Deformable Registration 
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.


  1. 1.
    Schmidt, G.P., Reiser, M.F., Baur-Melny, A.: Whole-body imaging of the musculoskeletal system: the value of MR imaging. Skel. Rad. 36(12), 1109–1119 (2007)CrossRefGoogle Scholar
  2. 2.
    Lauenstein, T.C., Goehde, S.C., Herborn, C.U., Goyen, M., Oberhoff, C., Debatin, J.F., Ruehm, S.G., Barkhausen, J.: Whole-Body MR Imaging: Evaluation of Patients for Metastases. Radiology 233(1), 139–148 (2004)CrossRefGoogle Scholar
  3. 3.
    Goyen, M.: Real Whole Body MRI: Requirements, Indications, Perspectives. McGraw-Hill, New York (2007)Google Scholar
  4. 4.
    Doran, S., Charles-Edwards, L., Reinsberg, S., Leach, M.: A complete distortion correction for MR images: I. Gradient warp correction. Physics in Medicine and Biology 50(7), 1343–1361 (2005)CrossRefGoogle Scholar
  5. 5.
    Chang, H., Fitzpatrick, J.: A technique for accurate magnetic resonance imaging in the presence of field inhomogeneities. IEEE TMI 11(3), 319–329 (1992)Google Scholar
  6. 6.
    Kannengiesser, S., Wang, Y., Haacke, E.: Geometric distortion correction in gradient-echo imaging by use of dynamic time warping. Magnetic Resonance in Medicine 42(3), 585–590 (1999)CrossRefGoogle Scholar
  7. 7.
    Reinsberg, S., Doran, S., Charles-Edwards, E., Leach, M.: A complete distortion correction for MR images: II. Rectification of static-field inhomogeneities by similarity-based profile mapping. Phys. Med. Biol. 50(11), 2651–2661 (2005)CrossRefGoogle Scholar
  8. 8.
    Rueckert, D., Sonoda, L., Hayes, C., Hill, D., Leach, M., Hawkes, D.: Nonrigid registration using free-form deformations: application to breast mr images. IEEE Transactions on Medical Imaging 18(8), 712–721 (1999)CrossRefGoogle Scholar
  9. 9.
    Glocker, B., Komodakis, N., Paragios, N., Tziritas, G., Navab, N.: Inter and intra-modal deformable registration: Continuous deformations meet efficient optimal linear programming. In: Karssemeijer, N., Lelieveldt, B. (eds.) IPMI 2007. LNCS, vol. 4584, pp. 408–420. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  10. 10.
    Joshi, S., Davis, B., Jomier, M., Gerig, G.: Unbiased diffeomorphic atlas construction for computational anatomy. NeuroImage 23, 151–160 (2004)CrossRefGoogle Scholar
  11. 11.
    Li, S.Z.: Markov random field modeling in image analysis. Springer, New York (2001)CrossRefzbMATHGoogle Scholar
  12. 12.
    Komodakis, N., Tziritas, G., Paragios, N.: Fast, approximately optimal solutions for single and dynamic mrfs. In: CVPR (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Christian Wachinger
    • 1
  • Ben Glocker
    • 1
    • 3
  • Jochen Zeltner
    • 2
  • Nikos Paragios
    • 3
  • Nikos Komodakis
    • 4
  • Michael Sass Hansen
    • 5
  • Nassir Navab
    • 1
  1. 1.Computer Aided Medical Procedures (CAMP)TUMMunichGermany
  2. 2.Siemens Medical SolutionsErlangenGermany
  3. 3.Mathématiques Appliquées aux Systèmes (MAS)Ecole Centrale ParisFrance
  4. 4.Computer Science DepartmentUniversity of CreteGreece
  5. 5.Technical University ofDenmark

Personalised recommendations