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Volume rendering techniques have been used widely for high quality visualization of 3D data sets, especially in the fields of biomedical image processing. However, when rendering very large (out-of-core) volume data sets, the conventional in-core volume rendering algorithms cannot run efficiently due to the impossibility of fitting the entire input data in the internal memory of a computer. In order to solve this problem, an efficient out-of-core volume rendering method based on volume ray casting and GPU acceleration, with a new out-of-core framework for visualizing large volume data sets, are proposed in this paper. The new framework gives a transparent and efficient access to the volume data set cached in the hard disk, while the new volume rendering method minimize the times of reloading volume data from the hard disk to the internal memory and perform comparatively fast high-quality volume rendering. The experimental results indicate that the new method and framework are effective and efficient for the visualization of out-of-core medical data sets.
Date of Conference: 20-21 Sept. 2009