In the field of Materials Science, tomographic images play an important role in the analysis of composite materials.We present a computational environment that helps specialists in the field to carry out analysis and evaluation of samples of composite materials.This environment takes the form of a tailored Problem Solving Environment (PSE) and builds upon the SCiRun PSE.Its implementation is driven primarily by four major attributes: modularity, flexibility, interactivity and performance.Users can easily assemble networks of modules, with some of the modules being specifically designed for materials science analysis.These modules are flexible in terms of configuration, so yielding more flexibility to the setup of the networks, as well as in relation to the user interaction upon them once running.The implementation of data processing algorithms supporting critical modules rely on parallel programming.Furthermore, the quality of tomographic images under analysis is an issue of concern.

This paper proposes a modification of the Marching Cubes algorithm for isosurfacing, with the intent of improving the representation of the surface in the interior of each grid cell. Our objective is to create a representation which correctly models the topology of the trilinear interpolant within the cell and which is robust under perturbations of the data and threshold value. To achieve this, we identify a small number of key points in the cell interior that are critical to the surface definition. This allows us to efficiently represent the different topologies that can occur, including the possibility of "tunnels." The representation is robust in the sense that the surface is visually continuous as the data and threshold change in value. Each interior point lies on the isosurface. Finally, a major feature of our new approach is the systematic method of triangulating the polygon in the cell interior.