This paper introduces a novel technique to compute illumination for Direct Volume Rendering. By adding shadow effects to volume rendered images, the perception of shapes and tissue properties can be significantly improved and it has the potential to increase the diagnostic value of medical volume rendering. The integrated intensity of incident light for a voxel is computed using a local approximation of the ambient occlusion, thus avoiding the rendering of tissues with very low illumination. Luminous tissue effects are also introduced to enhance the illumination model, controlled through an emissive component in the transfer function. This effect allows the user to highlight specific structures and can give a better understanding of tissue density. Multiresolution volume management and GPU-based computation is used to significantly speed-up the calculations and to support large data sets. The scheme yields interactive frame rates for incrementally refined ambient and emissive illumination for arbitrary transfer function changes.

A novel technique for efficient computation of global light propagation in interactive DVR is presented in this paper. The approach is based on a combination of local shadows from the vicinity of each voxel with global shadows calculated at high resolution but stored in a sparser grid. The resulting intensities are then used as the initial illumination for an additional pass that computes first order scattering effects. The method captures global shadowing effects with enhanced shadows of near structures. A GPU framework is used to evaluate the illumination updates at interactive frame rates, using incremental refinements of the in-scattered light. 

This paper presents a novel technique to efficiently compute illumination for Direct Volume Rendering using a local approximation of ambient occlusion to integrate the intensity of incident light for each voxel. An advantage with this local approach is that fully shadowed regions are avoided, a desirable feature in many applications of volume rendering such as medical visualization. Additional transfer function interactions are also presented, for instance, to highlight specific structures with luminous tissue effects and create an improved context for semitransparent tissues with a separate absorption control for the illumination settings. Multiresolution volume management and GPU-based computation are used to accelerate the calculations and support large data sets. The scheme yields interactive frame rates with an adaptive sampling approach for incrementally refined illumination under arbitrary transfer function changes. The illumination effects can give a better understanding of the shape and density of tissues and so has the potential to increase the diagnostic value of medical volume rendering. Since the proposed method is gradient-free, it is especially beneficial at the borders of clip planes, where gradients are undefined, and for noisy data sets.

We present a novel approach to interactive and concurrent volume visualization of functional Magnetic Resonance Imaging (fMRI). While the patient is in the scanner, data is extracted in real-time using state-of-the-art signal processing techniques. The fMRI signal is treated as light emission when rendering a patient-specific high resolution reference MRI volume, obtained at the beginning of the experiment. As a result, the brain glows and emits light from active regions. The low resolution fMRI signal is thus effectively fused with the reference brain with the current transfer function settings yielding an effective focus and context visualization. The delay from a change in the fMRI signal to the visualization is approximately 2 seconds. The advantage of our method over standard 2D slice based methods is shown in a user study. We demonstrate our technique through experiments providing interactive visualization to the fMRI operator and also to the test subject in the scanner through a head mounted display.