121 citations · 327 across the 38 of their papers we have counts for
4 papers · 1 filter
Faster PET Reconstruction with Non-Smooth Priors by Randomization and Preconditioning
Matthias J. Ehrhardt, Pawel Markiewicz, Carola-Bibiane Schönlieb
Uncompressed clinical data from modern positron emission tomography (PET) scanners are very large, exceeding 350 million data points (projection bins). The last decades have seen t…
A geometric integration approach to nonsmooth, nonconvex optimisation
Erlend S. Riis, Matthias J. Ehrhardt, G. R. W. Quispel +1
The optimisation of nonsmooth, nonconvex functions without access to gradients is a particularly challenging problem that is frequently encountered, for example in model parameter…
Enhancing joint reconstruction and segmentation with non-convex Bregman iteration
Veronica Corona, Martin Benning, Matthias J. Ehrhardt +6
All imaging modalities such as computed tomography (CT), emission tomography and magnetic resonance imaging (MRI) require a reconstruction approach to produce an image. A common im…
A geometric integration approach to smooth optimisation: Foundations of the discrete gradient method
Matthias J. Ehrhardt, Erlend S. Riis, Torbjørn Ringholm +1
Discrete gradient methods are geometric integration techniques that can preserve the dissipative structure of gradient flows. Due to the monotonic decay of the function values, the…