Algorithms for 3-D segmentation and reconstruction of anatomical surfaces from magnetic resonance imaging (MRI) data are presented. The 3-D extension of the Marr-Hildreth operator is described, and it is shown that its zero crossings are related to anatomical surfaces. For an improved surface definition, morphological filters-dilation and erosion-are applied. From these contours, 3-D reconstructions of skin, bone, brain, and the ventricular system can be generated. Results obtained with different segmentation parameters and surface rendering methods are presented. The fidelity of the generated images comes close to anatomical reality. It is noted that both the convolution and the morphological filtering are computationally expensive, and thus take a long time on a general-purpose computer. Another problem is assigning labels to the constituents of the head; in the current implementation, this is done interactively.

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By integrating concepts of computer graphics and artificial intelligence, novel ways of representing medical knowledge become possible. They allow unprecedented possibilities ranging from three-dimensional interactive atlases to systems for surgery rehearsal.

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The newly developed system is a stable, fully operational simulator for sinus surgery based on standard PC hardware. Besides the limitations of a low-cost haptic device, the presented system is highly realistic regarding anatomy, visualization, manipulation, and the appearance of the tools. It is mainly intended for gaining surgical anatomy knowledge and for training navigation in a complex anatomical environment. Learning effects, including motor skills, have yet to be quantified.

For the 3D-reconstruction of organ surfaces from tomograms, a shading method based on the partial volume effect is presented. In contrast to methods based on the depth and/or the angle of the voxel surface, here the gray-level gradient along the surface is used for shading. It is shown, that at least for bone and soft tissue surfaces, the results are superior to conventional shading. This is due to the high dynamic range of the gray levels within a small spatial neighborhood.

A profound knowledge of anatomy and surgical landmarks of the temporal bone is a basic necessity for any otologic surgeon. Because this knowledge, so far, has been mostly taught by limited temporal bone drilling courses, our objective was to create a system for virtual petrous bone surgery that allows the realistic simulation of specific laterobasal surgical approaches. A major requirement was the development of an interactive drill-like tool, together with a new technique for realistic visualization of simulated cut surfaces. The system is based on a volumetric, high-resolution model of the temporal bone, derived from CT. Interactive volume cutting methods using a new multivolume scheme have been developed. In this scheme, cut regions are modeled independently in additional data volumes using voxelization techniques. The voxelization is adapted to successive cutting operations as needed for the simulation of a drill-like tool. A new visualization technique was developed for artifact-free rendering of sharp edges, as formed by the intersection of a cut and an object surface. The new multivolume visualization technique allows high-quality visualization of interactively generated cut surfaces. This is a necessity for a realistic simulation of petrous bone surgery. Our system therefore facilitates comprehension of the complex morphology, and enables the recognition of surgical landmarks, which is most important if injury to delicate organs (e.g., the facial nerve or auditory ossicles) is to be avoided. The system for virtual petrous bone surgery allows the simulation of specific surgical approaches with high-quality visualization. The user can learn about the complex three-dimensional anatomy of the temporal bone from the viewpoint of a real otosurgical procedure.