The tremendous pace of innovation in imaging technologies offers society a tantalizing array of potential methods for understanding the underlying mechanisms of disease progression, climate change, agricultural conditions, and the evolution of distant galaxy systems, to name just a few application areas. Imaging is enabling less invasive and more effective interventions in medicine, and improved clinical trial methodologies for determining therapeutic efficacy of new compounds faster and with fewer patients on experimental regimens. In other application areas, imaging methods are being advanced to address national security needs, to track environmental states, and to search for planets that have the potential to support life. While the application areas seeking imaging solutions are broad and varied, they are tied together by common technical issues related to the enormity of the data sets generated by modern imaging systems and the unique issues associated with the evaluation of imaging devices for their objective comparison and optimization.
More powerful tools and assessment strategies are needed for accurate and objective evaluation of emerging imaging technologies with fewer resources. These tools must include accurate computational models of the entire imaging chain: models for the objects at the front end of the systems, models of the physics of the image formation process, and, finally, the process by which inferences are optimally drawn from the resulting data sets. Imaging data sets can be extremely large, containing information in space, time, wavelength or energy, and possibly other dimensions as well. Tools for the rigorous, objective, quantitative evaluation of the entire chain, from objects to images to observers (human or machine algorithm) need to be advanced and promulgated to allow for comparisons of effectiveness of new imaging strategies under development. This Gordon Research Conference will provide a unique venue bringing together an interdisciplinary array of scientists with expertise in the fundamental mathematics and physics of imaging systems, computational modeling of imaging processes, and the multivariate statistical methods needed for analyzing "big data" to accelerate the pace of imaging-system development, evaluation, and adoption for maximum impact on public health and society as a whole.