Investigating measures for transfer function generation for visualization of MET biomedical data

Abstract

In this paper, the question of automatically setting transfer functions for volume images is further explored. More specifically, the focus is automatic visualization of Molecular Electron Tomography (MET) volume images using one-dimensional transfer functions. We investigate how well a few general measures based on density, gradient, curvature and connected component information are suited for generating these transfer functions. To assess this, an expert has set suitable transfer function levels manually and we have studied how these levels relate to different characteristics of the selected measures for 29 data sets. We have found that the measures can be used to automatically generate a transfer function used to visualize MET data, to give the user an approximate view of the components in the image.