Statistical Models of Shape and Spatial Relation-application to Hippocampus Segmentation

Saïd Ettaïeb, Kamel Hamrouni, Su Ruan


This paper presents a new method based both on Active Shape Model (ASM) and spatial distance model to segment brain structures. It combines two types of a priori knowledge: the structure shapes and the distances between them. This knowledge consists of shape and distance variability which are estimated during a training step. Then, the obtained models are used to guide simultaneously the evolution of initial structure shapes towards the target contours. The proposed models are applied to extract two hippocampal regions on coronal MRI of the brain. The obtained results are encouraging and show the performance of the proposed model.


  1. Cootes, T. F., Taylor, C. J., Cooper, D. H., and Graham J., 1995. Active Shape Models - Their Training and Application. Computer Vision and Image Understanding, vol.61, pp38-59.
  2. Freeman, J., 1975. The modeling of spatial relations. Computer Graphic and image processing, Vol. 4, pp. 156-171.
  3. Borillo, A., 1998. L'espace et son expression en français. Ophrys, Paris.
  4. Geraud, T., 1998. Segmentation des structures internes du cerveau en imagerie par résonnance magnétique tridimensionnelle. Thèse de Doctorat, Télécom paris.
  5. Bloch, I., Géraud, T., and Maître, H., 2003. Representation and fusion of heterogeneous fuzzy information in the 3d space for model-based structural recognitionapplication to 3d brain imaging. Artificial Intelligence, Vol. 148, pp. 141-175.
  6. Perchant, A., and Bloch, I., 2002. Fuzzy Morphisms between Graphs. Fuzzy Sets and Systems, Vol. 128, pp. 149-168.
  7. Colliot, O, 2003. Représentation, évaluation et utilisation de relations spatiales pour l'interprétation d'images. Application à la reconnaissance de structures anatomiques en imagerie médicale. Thèse de doctorat, Telecom Paris.
  8. Kass, M., Witikin, A., and Terzopoulos, D., 1987. Snakes: Active contour models. International Journal of Computer vision, vol.1, pp. 321-331.
  9. Hudelot, C., Atif, J., and Bloch, I., 2008. Fuzzy Spatial Relation Ontology for Image Interpretation. Fuzzy Sets and Systems, 159:1929-1951.
  10. Fouquier, G., 2010. Optimisation de séquences de segmentation combinant modèle structurel et focalisation de l'attention visuelle. Application à la reconnaissance de structures cérébrales dans des images 3D. Thèse de doctorat, Ecole Nationale Supérieure des Télécommunications.
  11. Ghassan, H., 1998. Active Shape Models - Part I: Modelling Shape and Gray Level Variations. Proceedings of the Swedish Symposium on Image Analysis.
  12. Pizer, S. M., Joshi, S., Thomas Fletcher, P., Styner, M., Tracton, G., and Chen, J. Z., 2001. Segmentation of Single-Figure Object by Deformable M-reps. MICCAI, vol.2208, pp.862-871.
  13. Pitiot, A., Toga, A. W., and Thompson, P. M., 2002. Adaptive Elastic Segmentation of Brain MRI via Shape-Model-Guided Evolutionary programming. IEEE TMI, vol.21, pp.910-923.
  14. Yang, J., Staib, L. H., and Duncan, J. S., 2004. NeighborConstrained Segmentation With Level Set Based 3-D Deformable Models. IEEE TMI, vol.23, pp.940-948.
  15. Shen, K., 2011. Automatic Segmentation and Shape Analysis of Human Hippocampus in Alzheimer's Disease. Thèse de Doctorat, Université De Bourgogne.
  16. Shen, D., Moffat, S., Resnick, S. M., and Davatzikos, C., 2002. Measuring Size and Shape of the Hippocampus in MR Images Using a Deformable Shape Model. Neuroimage, Vol.15-2, pp.422-434.
  17. Bailleul, J., Ruan, S., and Constans, J. M., 2007. Statistical Shape Model-based Segmentation of brain MRI Images. International Conference of the IEEE EMBS, Lyon, France, 2007.
  18. Rajeesh, J., Moni, R. S., and Palanikumar, S., 2001. A versatile algorithm for the automatic segmentation of hippocampus based on level set. International Journal of Biomedical Engineering and Technology.
  19. Babalola, K. O., Patenaude, B., Aljabar, P. , Schnabel, J., Kennedy, D., Crum, W., Smith, S., Cootes, T. F., Jenkinson, M., and Rueckert, D., 2008. Comparison and Evaluation of Segmentation Techniques for Subcortical Structures in Brain MRI. MICCAI.
  20. Aljabar, P., Heckemann, R., Hammers, A., Hajnal, J., and Rueckert, D., 2007. Classifier selection strategies for label fusion using large atlas databases. MICCAI.
  21. Babalola , K. O., Petrovic, V., Cootes, T. F., Taylor, J. C., Twining, J. C., Williams, T. G., and Mills, A., 2007. Automated segmentation of the caudate nuclei using active appearance models. In 3D Segmentation in the clinic: A grand challenge. Workshop Proceedings, MICCAI.
  22. Patenaude, B., Smith, S., Kennedy, D., and Jenkinson, M., 2007. Bayesian shape and appearance models. Technical report TR07BP1, FMRIB Centre - University of Oxford.
  23. Murgasova, M., Dyet, L., Edwards, A. D., Rutherford, M., Hajnal, J., and Rueckert, D., 2007. Segmentation of brain MRI in young children. Acad. Rad.
  24. Cootes, T. F., Edwards, G. J., and Taylor, C. J., 1998. Active appearance models. European Conference on Computer Vision, pp 484-498.

Paper Citation

in Harvard Style

Ettaïeb S., Hamrouni K. and Ruan S. (2014). Statistical Models of Shape and Spatial Relation-application to Hippocampus Segmentation . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-003-1, pages 448-455. DOI: 10.5220/0004658404480455

in Bibtex Style

author={Saïd Ettaïeb and Kamel Hamrouni and Su Ruan},
title={Statistical Models of Shape and Spatial Relation-application to Hippocampus Segmentation},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014)},

in EndNote Style

JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014)
TI - Statistical Models of Shape and Spatial Relation-application to Hippocampus Segmentation
SN - 978-989-758-003-1
AU - Ettaïeb S.
AU - Hamrouni K.
AU - Ruan S.
PY - 2014
SP - 448
EP - 455
DO - 10.5220/0004658404480455