As the demand for high resolution, high content imaging increases, the cost and challenges of acquiring, storing, processing, and analyzing today’s very large imaging data sets are even more rapidly increasing. Today, the most interesting and informative data sets are often left uncollected or unprocessed because there isn't sufficient time or resources. For example, one often has to choose between high-resolution static imaging versus lower resolution dynamic imaging because we are limited in the total number of data points we can collect within a given time period of interest. Compressive sensing is a new approach where incomplete sampling under certain circumstances can be used to accurately recover the full data set--roughly translated into more information from less data. This research focuses on developing and implementing compressive sensing methods for electron microscopy and spectrometry based imaging and microanalysis techniques to address some of the inherent data acquisition and processing challenges. Available instruments include several different focused ion beam scanning electron microscopes (FIB SEM), and x-ray energy dispersive spectrometers (XEDS) and computational resources.

 

key words

Compressive sensing; Compressive sampling; Electron microscopy; Microanalysis; FIB; SEM; EDS; Imaging; Image analysis;

Citizenship:  Open to U.S. citizens

Level:  Open to Postdoctoral applicants