Flexible GPU-Based Multi-Volume Ray-Casting

摘要

Using combinations of different volumetric datasets is becoming more common in scientific applications, especially medical environments such as neu-rosurgery where multiple imaging modalities are required to provide insight to both anatomical and functional structures in the brain. Such data sets are usually in different orientations and have different resolutions. Furthermore, it is often interesting, e.g. for surgical planning or intraoperative applications to add the visualization of foreign objects (e.g., surgical tools, reference grids, 3D measurement widgets). We propose a flexible framework based on GPU-accelerated ray-casting and depth peeling, that allows volume rendering of multiple, arbitrarily positioned volumes intersected with opaque or translucent geometric objects. These objects can also be used as convex or concave clipping shapes. We consider the main contribution of our work to be the flexible combination of the above-mentioned features in a single framework. As such, it can serve as a basis for neurosurgery applications but also for other fields where multi-volume rendering is important.