GPU-based Object-Order Ray-Casting for Large Datasets

Abstract

We propose a GPU-based object-order ray-casting algorithm for the rendering of large volumetric datasets, such as the Visible Human CT datasets. A volumetric dataset is decomposed into small sub-volumes, which are then organized using a min-max octree structure. The small sub-volumes are stored in the leaf nodes of the min-max octree, which are also called cells. The cells are classified using a transfer function, and the visible cells are then loaded into the video memory or the AGP memory. The cells are sorted and projected onto the image plane front to back. The cell projection is implemented using a volumetric ray-casting algorithm on the GPU. In order to make the cell projection more efficient, we devise a propagation method to sort cells into layers. The cells within the same layer are projected at the same time. We demonstrate the efficiency of our algorithm using the Visible Human datasets and a segmented photographic brain dataset on commodity PCs.