Direct Visualization Of Surfaces From Computed Tomography Data

The application of direct volume visualization techniques to the presentation of CT data is explored. No surface detection or fitting of geometric primitives is involved. Images are formed by directly shading each data sample and projecting it onto the picture plane. The visualizations in this study are based on a hybrid physical model incorporating aspects of both surfaces and semi-transparent gels. Using a surface model, shading calculations are performed at every voxel with local gradient vectors serving as surface normals. In a separate step, surface classification and enhancement operators are applied to obtain a partial opacity for every voxel. Independence of shading and classification calculations insures an undistorted presentation of 3-D shape. The use of non-binary classification operators insure that small or poorly defined features are not lost. The resulting colors and opacities are merged from back to front along view rays using volumetric compositing, an approximation to the visibility calculations required to render a semi-transparent gel. The technique is simple and fast, yet produces images exhibiting smooth surface silhouettes and few other aliasing artifacts. The use of selective blurring and super-sampling to further improve image quality is also described.