Retrospective case series, Level IV.

No abstract

Background: Diffusion tensor imaging provides information about the location of white matter tracts within the human brain. For neurosurgery, this imaging technique is of major interest in order to minimize the risk of postoperative neurological deficits. In preoperative planning, fiber tracking algorithms based on streamline propagation are used in order to reconstruct major fiber tracts. The resulting streamline bundles approximate the course of the underlying white matter structures and indicate their shape and location in 3 dimensions as well as the spatial relation with respect to surrounding anatomy. However, for intraoperative application in combination with the neuronavigation system, these streamline representations are not adequate. Hulls encompassing the streamline bundles are necessary, since the boundary curves of hulls can be superimposed on the operating room (OR) microscope view for guidance in neurosurgery. Methods: In this work, we present a novel hull approach which is based on rasterization and isosurface extraction, combined with surface filtering techniques. The advantages of this approach are its robustness and the possibility to control the tightness of wrapping. Results: The approach makes it possible to generate precise hulls for different tract systems, which can be used as a basis for intraoperative visualization in the OR microscope. Distance measurements further confirm the accuracy of the hulls.

No abstract

Figure 1: First three levels and final result of our hierarchical iso-surface extraction algorithm. AbstractThe extraction and display of iso-surfaces is a standard method for the visualization of volume data sets. In this paper we present a novel approach that utilizes a hierarchy on both the input and the output data. For the generation of a coarse base mesh, we construct a hierarchy of volumes and extract an iso-surface from the coarsest resolution with a standard Marching Cubes algorithm. We additionally apply a simple mesh decimation algorithm to improve the shape of the triangles. We iteratively fit this mesh to the iso-surface at the finer volume levels. To be able to reconstruct fine detail of the iso-surface we thereby adaptively subdivide the mesh. To evenly distribute the vertices of the triangle mesh over the iso-surface and generate a triangle mesh with evenly shaped triangles, we have integrated a mesh smoothing algorithm into the fitting process. The advantage of this approach is that it generates a mesh with subdivision connectivity which can be utilized by several multiresolution algorithms such as compression and progressive transmission. As applications of our method we show how to reconstruct the surface of archaeological artifacts and the reconstruction of the brain surface for the simulation of the brain shift phenomenon.