Segmentation with Active Contours
Fabien Pierre, Mathieu Amendola, Clémence Bigeard, Timothé Ruel, Pierre-Frédéric Villard
⚠ This is a preprint. It may change before it is accepted for publication.


Active contours (also known as snakes) have shown their ability to introduce regularity on binary image segmentation. In contrast with level-set approaches, they are able to maintain the initial topology of the area of interest. For this reason, it has been used in recent medical research for diaphragm segmentation. Most of the on-line codes for 3D segmentation, as well as built-in Matlab toolboxes are based on level-set methods. Moreover, in the literature, the implementation details of active contours methods with meshes in three dimensions are tight, making tedious any reproduction of these techniques. In this paper, we propose some details on the implementation of active contours in 3D, especially on the choice of the use of a 3D mesh and its refinement. We also explore the choice of the parameters with a quantitative study of their influence on the segmentation results. The 3D segmentation method has been applied to CT scan images of the lungs.