A Semi-Automatic Surface Reconstruction Framework Based on T-Surfaces and Isosurface Extraction Methods

Abstract. In this paper we present a new approach which integrates the T-Surfaces model and isosurface generation methods in a general framework for surface reconstruction in 3D medical images. T-Surfaces is a deformable model based on a triangulation of the image domain, a discrete surface model and an image threshold. Two types of isosurface generation methods are considered: the continuation ones and the marching ones. The former is useful during the reparameterization of T-Surfaces while the later is suitable to initialize the model closer the boundary. Specifically, in a first stage, the T-Surfaces grid and the threshold are used to define a coarser image resolution. This field is thresholded to get a 0-1 function which is processed by a marching method to generate polygonal surfaces whose interior may contain the desired objects. If a polygonal surface involves more than one object, then the resolution is increased in that region and the marching applied again. Next, we apply T-Surfaces to improved the result. If the obtained topology remains incorrect, we enable the user to modify the topology by an interactive method based on the T-Surfaces framework. Finally, we demonstrate the utility of diffusion methods for our approach.