A New Landmark-Independent Tool for Quantifying and Characterizing Morphologic Variation

  • S. M. RolfeEmail author
  • L. L. Cox
  • L. G. Shapiro
  • T. C. Cox
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8814)


This paper develops a landmark-independent, deformable-registration-based framework that can utilize 3D surface images generated by any multidimensional imaging modality. The framework provides compact representations of image differences that are used to assess and compare potentially biologically relevant changes in 3D shape. The utility and sensitivity of the tools developed in this work are demonstrated using similarity retrieval of shape changes in a normal developmental time series of chick embryos. The results motivate future use of these tools for defining trajectories of normal growth, aiding research into conditions causing disruptions to normal growth.


Biomedical imaging Feature extraction Mathematical morphology Image representation and models 


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  1. 1.
    Ashburner, J., Hutton, C., Frackowiak, R., Johnsrude, I., Price, C., Friston, K.: Identifying global anatomical differences: deformation-based morphometry. Human Brain Mapping 6(5–6), 348–357 (1998)CrossRefGoogle Scholar
  2. 2.
    Birchfield, S.T., Rangarajan, S.: Spatiograms versus histograms for region-based tracking. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005, vol. 2, pp. 1158–1163. IEEE (2005)Google Scholar
  3. 3.
    Crum, W.R., Hartkens, T., Hill, D.L.G.: Non-rigid image registration: theory and practice. British Journal of Radiology 77(Special Issue 2), S140 (2004)CrossRefGoogle Scholar
  4. 4.
    Hamburger, V., Hamilton, H.L.: A series of normal stages in the development of the chick embryo. Journal of Morphology 88(1), 49–92 (1951)CrossRefGoogle Scholar
  5. 5.
    Lyons, D.M.: Sharing landmark information using mixture of gaussian terrain spatiograms. In: Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 5603–5608. IEEE Press (2009)Google Scholar
  6. 6.
    Müller, H., Marchand-Maillet, S., Pun, T.: The truth about corel - evaluation in image retrieval. In: Lew, M., Sebe, N., Eakins, J.P. (eds.) CIVR 2002. LNCS, vol. 2383, pp. 38–49. Springer, Heidelberg (2002) CrossRefGoogle Scholar
  7. 7.
    Ólafsdóttir, H., Darvann, T.A., Hermann, N.V., Oubel, E., Ersboll, B.K., Frangi, A.F., Larsen, P., Perlyn, C.A., Morriss-Kay, G.M., Kreiborg, S.: Computational mouse atlases and their application to automatic assessment of craniofacial dysmorphology caused by the crouzon mutation fgfr2c342y. Journal of Anatomy 211(1), 37–52 (2007)CrossRefGoogle Scholar
  8. 8.
    Rolfe, S.M., Camci, E.D., Mercan, E., Shapiro, L.G., Cox, T.C.: A new tool for quantifying and characterizing asymmetry in bilaterally paired structures. In: 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 2364–2367. IEEE (2013)Google Scholar
  9. 9.
    Rolfe, S.M., Shapiro, L.G., Cox, T.C., Maga, A.M., Cox, L.L.: A landmark-free framework for the detection and description of shape differences in embryos. In: 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC, pp. 5153–5156. IEEE (2011)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • S. M. Rolfe
    • 1
    Email author
  • L. L. Cox
    • 3
    • 4
  • L. G. Shapiro
    • 1
    • 2
  • T. C. Cox
    • 3
    • 4
    • 5
  1. 1.Departments of Electrical EngineeringUniversity of WashingtonSeattleUSA
  2. 2.Departments of Computer ScienceUniversity of WashingtonSeattleUSA
  3. 3.Departments of PediatricsUniversity of WashingtonSeattleUSA
  4. 4.Seattle Children’s Research InstituteSeattleUSA
  5. 5.Department of Anatomy and Developmental BiologyMonash UniversityClaytonAustralia

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