B. Van-ginneken, T. Heimann, and M. Styner, 3d segmentation in the clinic : A grand challenge, 2007.

M. Kass, A. Witkin, and D. Terzopoulos, Snakes: Active contour models, International Journal of Computer Vision, vol.5, issue.6035, pp.321-331, 1988.
DOI : 10.1007/BF00133570

T. Mcinerney and D. Terzopoulos, Deformable models in medical image analysis, Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis, pp.171-180, 1996.
DOI : 10.1109/MMBIA.1996.534069

J. Mykkänen, J. Tohka, J. Luoma, and U. Ruotsalainen, Automatic extraction of brain surface and mid-sagittal plane from PET images applying deformable models, Computer Methods and Programs in Biomedicine, vol.79, issue.1, pp.1-17, 2005.
DOI : 10.1016/j.cmpb.2005.03.003

J. G. Brankov, Y. Yang, and M. N. Wernick, Spatiotemporal processing of gated cardiac SPECT images using deformable mesh modeling, Medical Physics, vol.8, issue.9, p.2839, 2005.
DOI : 10.1088/0031-9155/43/4/015

H. Li, W. L. Thorstad, K. J. Biehl, R. Laforest, Y. Su et al., A novel PET tumor delineation method based on adaptive region-growing and dual-front active contours, Medical Physics, vol.13, issue.8, p.3711, 2008.
DOI : 10.1109/42.363096

C. Xu and J. L. Prince, Snakes, shapes, and gradient vector flow, Image Processing IEEE Transactions on, vol.7, issue.3, pp.359-369, 1998.

C. Xu and J. L. Prince, Generalized gradient vector flow external forces for active contours, Signal Processing, vol.71, issue.2, pp.131-139, 1998.
DOI : 10.1016/S0165-1684(98)00140-6

B. Li and S. T. Acton, Active Contour External Force Using Vector Field Convolution for Image Segmentation, IEEE Transactions on Image Processing, vol.16, issue.8, pp.2096-2106, 2007.
DOI : 10.1109/TIP.2007.899601

J. Cheng and S. W. Foo, Dynamic directional gradient vector flow for snakes, IEEE Transactions on Image Processing, vol.15, issue.6, pp.1563-1571, 2006.
DOI : 10.1109/TIP.2006.871140

X. Xie and M. Mirmehdi, Mac : Magnetostatic active contour model Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.30, issue.4, pp.632-646, 2008.
DOI : 10.1109/tpami.2007.70737

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

S. Y. Yeo, X. Xie, I. Sazonov, and P. Nithiarasu, Geometrically induced force interaction for three-dimensional deformable models, Image Processing IEEE Transactions on, vol.20, issue.5, pp.1373-1387, 2011.

J. Canny, A computational approach to edge detection Pattern Analysis and Machine Intelligence, IEEE Transactions on, issue.6, pp.679-698, 1986.

S. and D. Zenzo, A note on the gradient of a multi-image, Computer Vision, Graphics, and Image Processing, vol.33, issue.1, pp.116-125, 1986.
DOI : 10.1016/0734-189X(86)90223-9

H. C. Lee and D. R. Cok, Detecting boundaries in a vector field, IEEE Transactions on Signal Processing, vol.39, issue.5, pp.1181-1194, 1991.
DOI : 10.1109/78.80971

G. Sapiro, Vector (self) snakes: a geometric framework for color, texture, and multiscale image segmentation, Proceedings of 3rd IEEE International Conference on Image Processing, pp.817-820, 1996.
DOI : 10.1109/ICIP.1996.559624

X. Xie and M. Mirmehdi, RAGS: Region-Aided Geometric Snake, IEEE Transactions on Image Processing, vol.13, issue.5, pp.640-652, 2004.
DOI : 10.1109/TIP.2004.826124

L. D. Cohen and I. Cohen, Finite-element methods for active contour models and balloons for 2-d and 3-d images Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.15, issue.11, pp.1131-1147, 1993.

P. Blomgren and T. F. Chan, Color TV: total variation methods for restoration of vector-valued images, IEEE Transactions on Image Processing, vol.7, issue.3, pp.304-309, 1998.
DOI : 10.1109/83.661180

B. Li and S. T. Acton, Automatic active model initialization via poisson inverse gradient, Image Processing IEEE Transactions on, vol.17, issue.8, pp.1406-1420, 2008.

W. E. Lorensen and H. E. Cline, Marching cubes: A high resolution 3D surface construction algorithm, ACM SIGGRAPH Computer Graphics, vol.21, issue.4, pp.163-169, 1987.
DOI : 10.1145/37402.37422

G. Taubin, A signal processing approach to fair surface design, Proceedings of the 22nd annual conference on Computer graphics and interactive techniques , SIGGRAPH '95, pp.351-358, 1995.
DOI : 10.1145/218380.218473

S. Jan, G. Santin, D. Strul, S. Staelens, K. Assie et al., GATE: a simulation toolkit for PET and SPECT, Physics in Medicine and Biology, vol.49, issue.19, p.4543, 2004.
DOI : 10.1088/0031-9155/49/19/007

URL : https://hal.archives-ouvertes.fr/in2p3-00021834

I. George-zubal, R. Charles, . Harrell, O. Eileen, Z. Smith et al., Computerized three-dimensional segmented human anatomy Medical Physics-New York-Institute of Physics, pp.299-302, 1994.

D. P. Huttenlocher, G. A. Klanderman, and W. J. Rucklidge, Comparing images using the hausdorff distance Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.15, issue.9, pp.850-863, 1993.

M. P. Dubuisson and A. K. Jain, A modified Hausdorff distance for object matching, Proceedings of 12th International Conference on Pattern Recognition, pp.566-568, 1994.
DOI : 10.1109/ICPR.1994.576361