Locally Switching Between Cost Functions in Iterative Non-rigid Registration

  • William Mullally
  • Margrit Betke
  • Carissa Bellardine
  • Kenneth Lutchen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3765)


In non-rigid image registration problems, it can be difficult to construct a single cost function that adequately captures concepts of similarity for multiple structures, for example when one structure changes in density while another structure does not. We propose a method that locally switches between cost functions at each iteration of the registration process. This allows more specific similarity criteria to be embedded in the registration process and prevents costs from being applied to structures for which they are inappropriate. We tested our method by registering chest computed tomography (CT) scans containing a healthy lung to scans of the same lung afflicted with acute respiratory distress syndrome (ARDS). We evaluated our method both visually and with the use of landmarks and show improvement over existing methodology.


Cost Function Acute Respiratory Distress Syndrome Image Registration Cost Switching Registration Process 
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  1. 1.
    Lester, H., Arridge, S.R.: A survey of hierarchical non-linear medical image registration. Pattern Recognition 32, 129–149 (1999)CrossRefGoogle Scholar
  2. 2.
    Audette, M.A., Ferrie, F.P., Peters, T.M.: An algorithmic overview of surface registration techniques for medical imaging. Med Image Anal 4(3), 201–217 (2000)CrossRefGoogle Scholar
  3. 3.
    Mäkelä Timo, P., Clarysse, O., Sipilä, N., Pauna, Q.C., Pham, T.: Katila, and I. E. Magnin. A review of cardiac image registration methods. IEEE Trans Med Imag 21(9), 1011–1021 (2002)CrossRefGoogle Scholar
  4. 4.
    Pluim, J.P.W., Maintz, J.B.A., Viergever, M.A.: Mutual-information-based registration of medical images: A survey. IEEE Trans Med Imag 22(8), 986–1003 (2003)CrossRefGoogle Scholar
  5. 5.
    Betke, M., Hong, H., Thomas, D., Prince, C., Ko, J.P.: Landmark detection in the chest and registration of lung surfaces with an application to nodule registration. Med Image Anal 7(3), 265–281 (2003)CrossRefGoogle Scholar
  6. 6.
    Boldea, V., Sarrut, D., Clippe, S.: Lung deformation estimation with non-rigid registration for radiotherapy treatment. In: Ellis, R.E., Peters, T.M. (eds.) MICCAI 2003. LNCS, vol. 2878, pp. 770–777. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  7. 7.
    Bricault, I., Ferretti, G., Cinquin, P.: Registration of real and CT-derived virtual bronchoscopic images to assist transbronchial biopsy. IEEE Trans Med Imag 17(5), 703–714 (1998)CrossRefGoogle Scholar
  8. 8.
    Li, B.: The construction of a normative human lung atlas by inter-subject registration and warping of CT images. PhD thesis, The University of Iowa (2004)Google Scholar
  9. 9.
    Yu, J.N., Rahey, F.H., Gage, H.D., Eades, C.G., Harkness, B.A., Pelizzari, C.A., Keyes Jr., J.W.: Intermodality, retrospective image registration in the thorax. The Journal of Nuclear Medicine 36(12), 2333–2338 (1995)Google Scholar
  10. 10.
    Udobi, K.F., Childs, E., Touijer, K.: Acute respiratory distress syndrome. American Family Physician 67(2), 315–322 (2003)Google Scholar
  11. 11.
    Bellardine, C.L., Ingenito, E.P., Hoffman, A., Lopez, F., Sandborn, W., Suki, B., Lutchen, K.R.: Relating heterogeneous mechanics to gas exchange function during mechanical ventilation. Annls. Biomed. Eng (2005) (in press)Google Scholar
  12. 12.
    Rueckert, D., Sonoda, L.I., Hayes, C., Hill, D.L.G., Leach, M.O., Hawkes, D.J.: Nonrigid registration using free-form deformations: Application to breast MR images. IEEE Trans Med Imag 18(8), 712–721 (1999)CrossRefGoogle Scholar
  13. 13.
    Rohlfing, T., Maurer, C.R., Bluemke, D.A., Jacobs, M.A.: Volume-preserving nonrigid registration of MR breast images using free-form deformation with an incompressibility constraint. IEEE Trans Med Imag 22(6), 730–741 (2003)CrossRefGoogle Scholar
  14. 14.
    Shen, D., Davatzikos, C.: Hammer: Hierarchical attribute matching mechanism for elastic registration. IEEE Trans Med Imag 21(11), 1421–1439 (2002)CrossRefGoogle Scholar
  15. 15.
    Guest, E., Berry, E., Baldock, R.A., Fidrich, M., Smith, M.A.: Robjust point correspondence applied to two- and three- dimensional image registration. IEEE Trans Pattern Anal Mach Intell 23(2), 165–179 (2001)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • William Mullally
    • 1
  • Margrit Betke
    • 1
  • Carissa Bellardine
    • 2
  • Kenneth Lutchen
    • 2
  1. 1.Computer Science DepartmentBoston University 
  2. 2.Department of Biomedical EngineeringBoston UniversityBostonUSA

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