Volume visualization using relative distance among voxels

The aim of this work is to visualize 3D objects in volume data with minimum numbers of user-defined model or parameters. In this report, we propose a novel method that utilizes the distances along the optimum paths between a seed voxel in a target object and other voxels. The distance is defined using gradient between adjacent voxels or using difference between the seed voxel and other voxels along the optimum path. The optimization of a path is carried out by selecting the path where the largest value of absolute gradient or difference along a path is minimum, and the distance of each voxel is the largest value along the optimum path. The visualization is performed by rendering the volume where the initial voxel values are replaced with the distances. By the proposed method, the volume visualization can be accomplished only by setting a seed voxel in the target object. From experiments for visualizing human embryos obtained with MR microscopy, we confirmed that the proposed method successfully visualized the objects.