This paper presents a new method to find minimal paths in 3D images, giving as initial data one or two endpoints. This is based on previous work [1] for extracting paths in 2D images using Fast Marching [4]. Our original contribution is to extend this technique to 3D, and give new improvements of the approach that are relevant in 2D as well as in 3D. We also introduce several methods to reduce the computation cost and the user interaction. This work finds its motivation in the particular case of 3D medical images. We show that this technique can be efficiently applied to the problem of finding a centered path in tubular anatomical structures with minimum interactivity, and we apply it to path construction for virtual endoscopy. Synthetic and real medical images are used to illustrate each contribution. keywords : Deformable Models, Minimal paths, Level Set methods, Medical image understanding, Eikonal Equation, Fast Marching.
Thomas Deschamps, Laurent D. Cohen