We consider the efficient numerical minimization of Tikhonov functionals with nonlinear operators and non-smooth and non-convex penalty terms, which appear e.g. in variational regularization. For this, we consider a new class of SCD semismooth$^*$ Newton methods, which are based on a novel concept of graphical derivatives, and exhibit locally superlinear convergence. We present a detailed...
Elastography, as an imaging modality in general, aims at mapping the mechanical properties of a given material sample. For estimating the values of stiffness and strain quantitatively, we look at Elastography from the perspective of Inverse Problems. In particular, we start with theoretical ideas on how to perform Elastography and continue all the way to implementing Optical Coherence...
