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Non-convex optimisation in the imaging sciences

Organizers:
Martin Benning (University of Lubeck), Carola Schonlieb, and Tuomo Valkonen (University of Cambridge)

Abstract:
Optimisation methods for inverse problems involving nonlinear forward operator have so far received little attention. Yet many applied inverse problems are naturally of this form. Examples include magnetic resonance imaging tasks such as diffusion tensor imaging and velocity imaging. Further non-convex optimisation problems in the imaging sciences arise from improved regularisation functionals, modelling our prior assumptions on image curvature or gradient statistics. This minisymposium discusses recent advances in numerical methods for non-convex optimisation and their applications in the imaging sciences.