An Optimal Ray Traversal Scheme for Visualizing Colossal Medical Volumes

Modern computers are unable to store in main memory the complete data of high resolution medical images. Even on secondary memory (disk), such large datasets are sometimes stored in a compressed form. At rendering time, parts of the volume are requested by the rendering algorithm and are loaded from disk. If one is not careful, the same regions may be (decompressed and) loaded to memory several times. Instead, a coherent algorithm should be designed that minimizes this thrashing and optimizes the time and effort spent to (uncompress and) load the volume. We present an algorithm that divides the volume into cubic cells, each (compressed and) stored on disk, in contrast to the more common slice-based storage. At rendering time, each cell is allocated a queue of rays. For a sequence of images, all rays are spawned and queued at the cells they intersect first. Cells are loaded, one at a time, in front-to-back (FTB) order. A loaded cell is rendered by all rays found in its queue. We analyze the algorithm in detail and demonstrate its advantages over existing ray casting volume rendering methods.