Abstract
Large biomedical volumetric data sets are usually stored as file sets, where the files represent a family of cross sections. Interactive rendering of large data sets requires fast access to user-defined parts of the data, because it is virtually impossible to render an entire data set of such an enormous size (several gigabytes) at full resolution, and to transfer such data upon request over the Internet in a reasonable amount of time. Therefore, hierarchical rendering techniques have been introduced to render a region of interest at a relatively higher resolution. Regions rendered at coarser resolutions are provided as context information. We present a dynamic subdivision scheme that incorporates space-subdivision and wavelet compression.
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Meyer, J., Borg, R., Hamann, B., Joy, K.I., Olson, A.J. (2003). Network-based Rendering Techniques for Large-scale Volume Data Sets. In: Farin, G., Hamann, B., Hagen, H. (eds) Hierarchical and Geometrical Methods in Scientific Visualization. Mathematics and Visualization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55787-3_17
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DOI: https://doi.org/10.1007/978-3-642-55787-3_17
Publisher Name: Springer, Berlin, Heidelberg
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