knowledge into modeling and assessment. In doing this, we should also consider how we might adapt our approaches in the future to address higher-dimensional images and advanced imaging methods and also how to improve statistical descriptions of the imaging chain (including the observer) to achieve adequate modeling. It is also worthwhile to consider whether some simple models might have the capacity to adequately inform performance assessment.
One practical and achievable goal is to design observer-based systems: Imaging systems could include settings for personalized optimization guided by real-time feedback including personalized error scores. Different imaging protocols could be optimized for each observer using realtime calculation of different views, displays, and contrasts with adjustable parameters. These personalized imaging systems would thus rely on both observer-based and task-based assessment, perhaps more effectively addressing system non-idealities.
These approaches, of course, need to be examined by a wide range of diverse communities. Nonlinear systems, which have potential high impact on imaging capabilities, may benefit most from some initial steps toward task-based assessment because of their complexity and current lack of sufficient methods for assessment. Such fields include compressed sensing, deblurring or deconvolution, nonlocal means filtering and estimation, and spatiotemporal methods.