Structural focus+context rendering of multiclassified volume data

Abstract

We present a F+C volume rendering system aimed at outlining structural relationships between different classification criteria of a multiclassified voxel model. We clusterize the voxel model into subsets of voxels sharing the same classification criteria and we construct an auxiliary voxel model storing for each voxel an identifier of its associated cluster. We represent the logical structure of the model as a directed graph having as nodes the classification criteria and as edges the inclusion relationships. We define a mapping function between nodes of the graph and clusters. The rendering process consists of two steps. First, given a user query defined in terms of a boolean expression of classification criteria, a parser computes a set of transfer functions on the cluster domain according to structural F+C rules. Then, we render simultaneously the original voxel model and the labelled one applying multimodal 3D texture mapping such that the fragment shader uses the computed transfer functions to apply structural F+C shading. The user interface of our system, based on Tulip, provides a visual feedback on the structure and the selection. We demonstrate the utility of our approach on several datasets.