J. A. Baerentzen and H. Aanaes, Signed distance computation using the angle weighted pseudonormal, IEEE Transactions on Visualization and Computer Graphics, vol.11, issue.3, pp.243-253, 2005.

Z. Chen and H. Zhang, Learning implicit fields for generative shape modeling, The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.

T. Demarcy, Segmentation and study of anatomical variability of the cochlea from medical images. Theses, 2017.
URL : https://hal.archives-ouvertes.fr/tel-01609910

S. Jia, A. Despinasse, Z. Wang, H. Delingette, X. Pennec et al., Automatically Segmenting the Left Atrium from Cardiac Images Using Successive 3D U-Nets and a Contour Loss, Statistical Atlases and Computational Modeling of the Heart (STACOM) workshop, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01860285

J. Huang, Y. Li, R. Crawfis, . Shao-chiung, S. Lu et al., A complete distance field representation, Proceedings Visualization, 2001. VIS '01, pp.247-561, 2001.

M. W. Jones, J. A. Baerentzen, and M. Sramek, 3d distance fields: a survey of techniques and applications, IEEE Transactions on Visualization and Computer Graphics, vol.12, issue.4, pp.581-599, 2006.

C. R. Maurer, R. Qi, and V. Raghavan, A linear time algorithm for computing exact euclidean distance transforms of binary images in arbitrary dimensions, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.25, issue.2, pp.265-270, 2003.

J. Park, P. Florence, J. Straub, R. Newcombe, and S. Lovegrove, Deepsdf: Learning continuous signed distance functions for shape representation, The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.

M. Kilian, J. Pohl, M. E. Fisher, R. W. Shenton, . Mccarley et al., Logarithm Odds Maps for Shape Representation. Medical image computing and computer-assisted intervention : MICCAI, International Conference on Medical Image Computing and Computer-Assisted Intervention, pp.955-963, 2006.

C. Quammen, C. Weigle, and R. Taylor, Boolean operations on surfaces in vtk without external libraries. VTK journal, 2011.

O. Ronneberger, P. Fischer, and T. Brox, U-net: Convolutional networks for biomedical image segmentation, vol.9351, pp.234-241

A. Roosing, O. Strickson, and N. Nikiforakis, Fast distance fields for fluid dynamics mesh generation on graphics hardware, 2019.

R. Tsai and S. Osher, Level set methods and their applications in image science, Communications in mathematical sciences, vol.1, 2003.

J. Wu and L. Kobbelt, Piecewise linear approximation of signed distance fields, Vision, Modeling and Visualization, pp.513-520, 2003.

Y. Wu, J. Man, and Z. Xie, A double layer method for constructing signed distance fields from triangle meshes, Graphical Models, vol.76, issue.4, pp.214-223, 2014.