A Study on Transfer Function Design for Direct Volume Rendering

Abstract

Although direct volume rendering (DVR) has become a commodity, the design of transfer functions still a challenge. Transfer functions which map data values to optical properties (i.e., colors and opacities) highlight features of interests as well as hide unimportant regions, dramatically impacting on the quality of the visualization. Therefore, for the effective rendering of interesting features, the design of transfer functions is very important and challenging task. Furthermore, manipulation of these transfer functions is tedious and time-consuming task. In this paper, we propose a 3D spatial field for accurately identifying and visually distinguishing interesting features as well as a mechanism for data exploration using multi-dimensional transfer function. First, we introduce a 3D spatial field for the effective visualization of constricted tubular structures, called as a stenosis map which stores the degree of constriction at each voxel. Constrictions within tubular structures are quantified by using newly proposed measures (i.e., line similarity measure and constriction measure) based on the localized structure analysis, and classified with a proposed transfer function mapping the degree of constriction to color and opacity. We show the application results of our method to the visualization of coronary artery stenoses. We present performance evaluations using twenty-eight clinical datasets, demonstrating high accuracy and efficacy of our proposed method. Second, we propose a new multi-dimensional transfer function which incorporates texture features calculated from statistically homogeneous regions. This approach employs parallel coordinates to provide an intuitive interface for exploring a new multi-dimensional transfer function space. Three specific ways to use a new transfer function based on parallel coordinates enables the effective exploration of large and complex datasets. We present a mechanism for data exploration with a new transfer function space, demonstrating the practical efficacy of our proposed method. Through a study on transfer function design for DVR, we propose two useful approaches. First method to saliently visualize the constrictions within tubular structures and interactively adjust the visual appearance of the constrictions delivers a substantial aid in radiologic practice. Furthermore, second method to classify objects with our intuitive interface utilizing parallel coordinates proves to be a powerful tool for complex data exploration.