Volume visualization using gradient-based distance among voxels

Abstract

The aim of this work is to visualize 3D objects in volume data with minimum numbers of user-defined models 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 here is defined using gradient between adjacent voxels along the path. The distance is also used as the criterion of path optimization. The visualization is carried out by rendering the volume where the initial voxel values are replaced with the distances. Experimental results for an image of human embryo obtained with MR microscopy have displayed the effectiveness of this method.