Focus + Context Rendering of Structured Biomedical Data

Abstract

Biomedical data can be classified according to different taxonomies. Understanding the relationships between different data categories is essential for an in-depth knowledge of the data. We present a volume rendering system aimed at outlining structural relationships between different classification criteria of a biomedical voxel model. The system clusterizes the model into subsets of voxels sharing the same classification criteria. It constructs a labelled voxel model storing for each voxel an identifier of its associated cluster. We represent the classification space as a graph and we render it in the application interface. This way, clinicians can specify their visualization queries by selecting nodes of the graph and boolean operations between them. Given a rendering query, the system computes a transfer function on the labelled voxel model domain. This transfer function, together with the original voxel model and the labelled voxel model, are used during rendering to visualize the selected data more or less colored according to level of the graph at which they have been selected, and contextualized with the other parts of the model to which they are related. We demonstrate the utility of our approach on several biomedical datasets.