Real-Time 3D Image Segmentation by User-Constrained Template Deformation

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7510)


We describe an algorithm for 3D interactive image segmentation by non-rigid implicit template deformation, with two main original features. First, our formulation incorporates user input as inside/outside labeled points to drive the deformation and improve both robustness and accuracy. This yields inequality constraints, solved using an Augmented Lagrangian approach. Secondly, a fast implementation of non-rigid template-to-image registration enables interactions with a real-time visual feedback. We validated this generic technique on 21 Contrast-Enhanced Ultrasound images of kidneys and obtained accurate segmentation results (Dice> 0.93) in less than 3 clicks in average.


Image Segmentation Active Shape Model Prior Shape Liver Segmentation Augmented Lagrangian Approach 
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  1. 1.
    Cootes, T.F., et al.: Active shape models: Their training and application. CVIU 61(1), 38–59 (1995)Google Scholar
  2. 2.
    Paragios, N., Rousson, M., Ramesh, V.: Matching Distance Functions: A Shape-to-Area Variational Approach for Global-to-Local Registration. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002, Part II. LNCS, vol. 2351, pp. 775–789. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  3. 3.
    Cremers, D., et al.: Towards recognition-based variational segmentation using shape priors and dynamic labeling. In: Scale Space, pp. 388–400 (2003)Google Scholar
  4. 4.
    Chan, T.F., Zhu, W.: Level set based shape prior segmentation. In: IEEE CVPR, pp. II:1164–II:1170 (2005)Google Scholar
  5. 5.
    Foulonneau, A., et al.: Multi-reference shape priors for active contours. IJCV 81(1), 68–81 (2009)CrossRefGoogle Scholar
  6. 6.
    Leventon, M.E., et al.: Statistical shape influence in geodesic active contours. In: IEEE CVPR, pp. 316–323 (2000)Google Scholar
  7. 7.
    Tsai, A., et al.: A shape-based approach to the segmentation of medical imagery using level sets. IEEE TMI 22(2), 137–154 (2003)Google Scholar
  8. 8.
    Bresson, X., et al.: A variational model for object segmentation using boundary information and shape prior driven by the Mumford-Shah functional. IJCV 68(2), 145–162 (2006)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Cremers, D., et al.: Shape statistics in kernel space for variational image segmentation. Pattern Recognition 36(9), 1929–1943 (2003)zbMATHCrossRefGoogle Scholar
  10. 10.
    Saddi, K.A., et al.: Global-to-local shape matching for liver segmentation in ct imaging. In: MICCAI (October 2007)Google Scholar
  11. 11.
    Somphone, O., Mory, B., Makram-Ebeid, S., Cohen, L.: Prior-Based Piecewise-Smooth Segmentation by Template Competitive Deformation Using Partitions of Unity. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part III. LNCS, vol. 5304, pp. 628–641. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  12. 12.
    Huang, X., Metaxas, D.: Metamorphs: Deformable shape and appearance models. IEEE Trans. PAMI 30(8), 1444–1459 (2008)CrossRefGoogle Scholar
  13. 13.
    Freedman, D., Zhang, T.: Interactive graph cut based segmentation with shape priors. In: CVPR, vol. 1, pp. 755–762 (June 2005)Google Scholar
  14. 14.
    Zhu, S.C., Yuille, A.: Region competition: Unifying snakes, region growing, and bayes/mdl for multiband image segmentation. PAMI 18(9), 884–900 (1996)CrossRefGoogle Scholar
  15. 15.
    Yezzi, A., Soatto, S.: Deformotion: Deforming motion, shape average and the joint registration and approximation of structures in images. IJCV 53(2), 153–167 (2003)CrossRefGoogle Scholar
  16. 16.
    Nocedal, J., Wright, S.J.: Numerical Optimization. Springer (August 1999)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Medisys, Philips ResearchSuresnesFrance

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