Advances in modern digital imaging methods are revolutionizing a wide range of scientific disciplines. They facilitate the acquisition of huge amounts of data that allow the visualization, measurement, reconstruction, and archiving of complex, multi-dimensional images. At the same time, advances in computing technologies enable the deployment of tremendous computing resources. This permits numerical modeling of a broad swath of scientific phenomena, and results in the production of vast quantities of numerical data. These data are just the beginning of the scientific exploration that modern computational and visualization methods will allow. But these advanced data generation capabilities require other enhanced abilities — with increasing data size and complexity, the development of more efficient acquisition and analysis methods is essential.
In this lecture, Lawrence R. Frank will discuss how this new paradigm of imaging exploration is manifest. He will explore how the increasing generality of approaches has led to dynamic methods for data analysis applicable to disparate fields, from brain imaging to severe weather.
Lawrence R. Frank received his Ph.D. in physics from the Massachusetts Institute of Technology. He is founder and director of the University of California, San Diego Center for Scientific Computation in Imaging (CSCI). His primary focus has been on the development of novel methods of magnetic resonance imaging (MRI) used in conjunction with computational methods. Used together, these methods address research questions in a variety of topics, such as cardiac biomechanics, evolutionary biology and characterization of neural architecture. The work at CSCI has recently expanded to the development of theoretical frameworks and computational methods for the analysis of spatial-temporal data in imaging for applications, from dynamic imaging of brain activity with functional MRI to severe weather meteorology.