Search Results for author: Jürgen Debus

Found 2 papers, 2 papers with code

Continuous-Time Deep Glioma Growth Models

2 code implementations • 23 Jun 2021 • Jens Petersen, Fabian Isensee, Gregor Köhler, Paul F. Jäger, David Zimmerer, Ulf Neuberger, Wolfgang Wick, Jürgen Debus, Sabine Heiland, Martin Bendszus, Philipp Vollmuth, Klaus H. Maier-Hein

The ability to estimate how a tumor might evolve in the future could have tremendous clinical benefits, from improved treatment decisions to better dose distribution in radiation therapy.

Time Series Time Series Analysis +1

Paper
Code

Deep Probabilistic Modeling of Glioma Growth

1 code implementation • 9 Jul 2019 • Jens Petersen, Paul F. Jäger, Fabian Isensee, Simon A. A. Kohl, Ulf Neuberger, Wolfgang Wick, Jürgen Debus, Sabine Heiland, Martin Bendszus, Philipp Kickingereder, Klaus H. Maier-Hein

Existing approaches to modeling the dynamics of brain tumor growth, specifically glioma, employ biologically inspired models of cell diffusion, using image data to estimate the associated parameters.

Representation Learning

Paper
Code

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