SGER: Volume Comparisons

体积数据是许多类型的科学和医学调查的重要组成部分。体积可视化提供了工具，帮助科学家检查体积数据：方法存在显示大量的数据集，并显示适度的数据集交互式使用商品硬件。提供假照明的合成外观方法和风格化（例如非真实感）渲染方法有助于使复杂形状更容易理解。然而，所有这些进展都集中在帮助科学家检查单个体积数据集的工具上，需要明确帮助科学家在体积数据集之间进行视觉比较的工具。例如，科学家可能需要找到两个标本之间的差异，或者在一系列体积中寻找趋势。随着数据生成吞吐量的增加，对此类工具的需求也将增长：扫描的激增意味着将扫描更多的标本;非侵入性成像技术允许在动物的发育过程中进行一系列扫描;基于网格的超级计算允许运行大量独立的模拟。

Volume data is a vital part of many types of scientific and medical inquiry. Volume visualization has provided tools to help scientists examine volume data: methods exist for display of massive datasets and to display moderate datasets interactively using commodity hardware. Synthetic appearance methods to provide fake lighting and stylized (e.g. non-photorealistic) rendering methods help make complex shapes easier to comprehend. However, all of these advances focus on tools to help a scientist examine a single volumetric dataset.There is a need for tools that explicitly help scientists make visual comparisons among volume datasets. For example, a scientist may need to find differences between two specimens or to look for trends in a sequence of volumes. The need for such tools will grow as the throughput of data generation increases: the proliferation of scanning means more specimens will be scanned; noninvasive imaging techniques allow for series of scans over the development of an animal; and grid-based supercomputing allows for large numbers of independent simulations to be run.