Quantitative non-destructive imaging with limited data

如果成像需要更少的数据，它将实现更快的吞吐量，在限制访问的情况下提高性能，以及更简单，更便宜的硬件。来自图像的信息可以在工程部件内准确量化损坏，避免在过度保守和不可预测的故障之间进行选择。为了能够从有限的数据集改进重建，已经确定了一组不同的方法，将物理波与物体相互作用的知识，外部信息的使用，图像处理和其他技术。该奖学金将通过将这些方法应用于几个行业非常感兴趣的示例应用程序来解决广泛的问题，并最终使有限数据成像领域的发展成为可能。虽然主要集中在NDE（非破坏性评估），但其应用扩展到包括医学，物理学和安全在内的领域。

If imaging required less data, it would enable faster throughput, improved performance in restricted access situations and simpler, cheaper hardware. The information from images enables damage to be accurately quantified within engineering components, avoiding the need to choose between excessive conservatism and unpredicted failures. To enable improved reconstructions from limited data sets, a diverse set of approaches have been identified, incorporating knowledge of physical wave interaction with objects, use of external information, image processing and other techniques. The fellowship will address the broad problem by applying these approaches to several example applications which are of great interest to industry, and will ultimately enable the development of the field of limited data imaging. While primarily focused on NDE (non-destructive evaluation), the applications of this spread to areas including medicine, geophysics and security.