In this paper, we have proposed the construction method of the geometry model of the brain tumor by the three-dimensional(3-D) Active Sphere. 3-D Active Sphere, which is a kind of the energy-minimizing method, is able to extract the three-dimensional geometry model directly from the volume data sequences composed of the MRI slice images. The method enables us more accurate and direct extraction of a three-dimensional geometry model than the previous energy-minimizing method, because both the boundary and the interior information are used for the modification of the object in our method.
3D Active Net, which is a 3D extension of Snakes, is an energy-minimizing surface model which can extract a volume of interest from 3D volume data. It is deformable and evolves in 3D space to be attracted to salient features, according to its internal and image energy. The net can be fitted to the contour of a target object by defining the image energy suitable for the contour property. We present testing results of the extraction of a muscle from the Visible Human Data by two methods: manual segmentation and the application of 3D Active Net. We apply principal component analysis, which utilizes the color information of the 3D volume data to emphasize an ill-defined contour of the muscle, and then apply 3D Active Net. We recognize that the extracted object has a smooth and natural contour in contrast with a comparable manual segmentation, proving an advantage of our approach.
We describe a neurosurgical planning support system that we developed on a workstation. It enables a surgeon to generate useful 3-D images interactively and to simulate surgery on the computed images pre-surgically to confirm the optimum parameters for the instruments used in stereotactic surgery. In particular, we introduce two techniques for implementing indispensable functions in systems like this. One is an algorithm that can detect boundaries in medical images, and the other is an algorithm that can reduce the volume of polygonal data for surface-rendered images. These techniques move our system a step toward clinical use.
In this paper, we propose a high-speed and direct imaging algorithm for constructing equi-valued surfaces from
3D grid data in scientific and enneering fields. Our basic idea is to generate and draw polygons simultaneously
by processing the cells spanned by grids in order of decreasing distance from the current viewpoint. Equi-valued
surfaces are generated in five tetrahedrons into which the cells are subdivided, and are sent to a graphics device.
The execution order of each of the tetrahedrons is identical and determined by the current viewpoint. Since the
algorithm does not need a store of intermediate polyhedral data, depth calculation, or depth buffer memory for
hidden surface removal, the user can get a quick response to changes of the view direction and of the surface constant
C in interactive graphics. This algorithm is particularly powerful for imaging multiple surfaces associated with
multiple surface constants in semi-transparent display.