Deformable meshes with automated topology changes for coarse-to-fine three-dimensional surface extraction

This work presents a generic deformable model for extracting objects from volumetric data with a coarse-to-fine approach. This model is based on a dynamic triangulated surface which alters its geometry according to internal and external constraints to perform shape recovery. A new framework for topology changes is proposed to extract complex objects: within this framework, the model dynamically adapts its topology to the geometry of its vertices according to simple distance constraints. In order to speed up the process, an algorithm of pyramid construction with any reduction factor transforms the image into a set of images with progressively higher resolutions. This organization into a hierarchy, combined with a model which can adapt its sampling to the resolution of the workspace, enables a fast estimation of the shapes included in the image. After that, the model searches for finer and finer details while relying successively on the different levels of the pyramid.