217 citations · 323 across the 10 of their papers we have counts for
7 papers · 1 filter
GEASI: Geodesic-based Earliest Activation Sites Identification in cardiac models
Thomas Grandits, Alexander Effland, Thomas Pock +3
The identification of the initial ventricular activation sequence is a critical step for the correct personalization of patient-specific cardiac models. In healthy conditions, the…
One-sided Frank-Wolfe algorithms for saddle problems
Vladimir Kolmogorov, Thomas Pock
We study a class of convex-concave saddle-point problems of the form where is a linear operator, is th…
PIEMAP: Personalized Inverse Eikonal Model from cardiac Electro-Anatomical Maps
Thomas Grandits, Simone Pezzuto, Jolijn M. Lubrecht +3
Electroanatomical mapping, a keystone diagnostic tool in cardiac electrophysiology studies, can provide high-density maps of the local electric properties of the tissue. It is ther…
Total Deep Variation for Linear Inverse Problems
Erich Kobler, Alexander Effland, Karl Kunisch +1
Diverse inverse problems in imaging can be cast as variational problems composed of a task-specific data fidelity term and a regularization term. In this paper, we propose a novel…
An Optimal Control Approach to Early Stopping Variational Methods for Image Restoration
Alexander Effland, Erich Kobler, Karl Kunisch +1
We investigate a well-known phenomenon of variational approaches in image processing, where typically the best image quality is achieved when the gradient flow process is stopped b…
A convex variational model for learning convolutional image atoms from incomplete data
Antonin Chambolle, Martin Holler Thomas Pock
A variational model for learning convolutional image atoms from corrupted and/or incomplete data is introduced and analyzed both in function space and numerically. Building on lift…