A level set formulation for Willmore flow

By Marc Droske, Martin Rumpf. 2004

135 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computer Graphics and Computer-Aided Design, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/664977f0617ed3635918b24482a325445c9cb7e0

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Mechanics

1. Gerhard Dziuk
2. Charles M. Elliott
3. Martin Burger
4. Stanley J. Osher
5. Christian Lubich
6. Ernst Hairer
7. Klaus Deckelnick
8. Xuecheng Tai

In Computer Graphics and Computer-Aided Design

1. Martin Burger
2. Charles M. Elliott
3. Gerhard Dziuk
4. Stanley J. Osher
5. Klaus Deckelnick
6. Michael Y. Wang
7. Ronald Fedkiw
8. Xavier Bresson

In Statistical and Nonlinear Physics

1. Martin Burger
2. Stanley J. Osher
3. Christian Lubich
4. Othmar Koch
5. Bart Vandereycken
6. André Uschmajew
7. Achim Nonnenmacher

Citations in the corpus

• A survey on level set methods for inverse problems and optimal design (2005, methodology): “Recently, level set based optimization methods have been used for the morphological registration of medical images by Droske & Rumpf [51, 129] and by Vemuri et al. [142], where objective functionals similar to elastic energies has been minimized using level set based gradient methods.”
• Computation of geometric partial differential equations and mean curvature flow (2005, background): “The above ideas were introduced by Droske and Rumpf (2004) for a level set approach to Willmore flow.”
• Energy-diminishing integration of gradient systems (2014, background): “…(Chafee & Infante (1974); Elliott & Zheng (1986)), the porous medium equation (Otto (2001)), models in image processing (Strzodka et al. (2004); Michailovich et al. (2007)), in differential geometry (Droske & Rumpf (2004); Bobenko & Schröder (2005)), and in quantum systems (Bao & Du (2004)).”