Abstract

Deformable models are by their formulation able to solve sur- face extraction problem from noisy volumetric images. This is since they use image independent information, in form of internal energy or internal forces, in addition to image data to achieve the goal. However, it is not a simple task to deform initially given surface meshes to a good repre- sentation of the target surface in the presence of noise. Several methods to do this have been proposed and in this study a few recent ones are compared. Basically, we supply an image and an arbitrary but reason- able initialization and examine how well the target surface is captured with difierent methods for controlling the deformation of the mesh. Ex- periments with synthetic images as well as medical images are performed and results are reported and discussed. With synthetic images, the qual- ity of results is measured also quantitatively. No optimal method was found, but the properties of di?erent methods in distinct situations were highlighted.