Real-time Bayesian personalization via a learnable brain tumor growth model. - Ivan Ezhov; Tudor Mot; Suprosanna Shit; Jana Lipková; Johannes C. Paetzold; Florian Kofler; Fernando Navarro; Marie Metz; Benedikt Wiestler; Björn H. Menze (CoRR, 2020)

A for-loop is all you need. For solving the inverse problem in the case of personalized tumor growth modeling. - Ivan Ezhov; Marcel Rosier; Lucas Zimmer; Florian Kofler; Suprosanna Shit; Johannes C. Paetzold; Kevin Scibilia; Felix Steinbauer; Leon Mächler; Katharina Franitza; Tamaz Amiranashvili; Martin J. Menten; et al. (ML4H@NeurIPS, 2022)

Casting the inverse problem as a database query. The case of personalized tumor growth modeling. - Ivan Ezhov; Marcel Rosier; Lucas Zimmer; Florian Kofler; Suprosanna Shit; Johannes C. Paetzold; Kevin Scibilia; Leon Mächler; Katharina Franitza; Tamaz Amiranashvili; Marie Metz; Sailesh Conjeti; et al. (CoRR, 2022)

Geometry-Aware Neural Solver for Fast Bayesian Calibration of Brain Tumor Models. - Ivan Ezhov; Tudor Mot; Suprosanna Shit; Jana Lipková; Johannes C. Paetzold; Florian Kofler; Chantal Pellegrini; Marcel Kollovieh; Fernando Navarro; Hongwei Li 004; Marie Metz; Benedikt Wiestler; et al. (IEEE Trans. Medical Imaging, 2022)

Primitive Simultaneous Optimization of Similarity Metrics for Image Registration. - Diana Waldmannstetter; Benedikt Wiestler; Julian Schwarting; Ivan Ezhov; Marie Metz; Spyridon Bakas; Bhakti Baheti; Satrajit Chakrabarty; Daniel Rueckert; Jan S. Kirschke; Rolf A. Heckemann; Marie Piraud; et al. (BrainLes/SWITCH@MICCAI, 2023)

Primitive Simultaneous Optimization of Similarity Metrics for Image Registration. - Diana Waldmannstetter; Florian Kofler; Benedikt Wiestler; Julian Schwarting; Ivan Ezhov; Marie Metz; Daniel Rueckert; Jan S. Kirschke; Marie Piraud; Bjoern H. Menze (CoRR, 2023)

Framing image registration as a landmark detection problem for better representation of clinical relevance. - Diana Waldmannstetter; Benedikt Wiestler; Julian Schwarting; Ivan Ezhov; Marie Metz; Spyridon Bakas; Bhakti Baheti; Satrajit Chakrabarty; Jan S. Kirschke; Rolf A. Heckemann; Marie Piraud; Florian Kofler; et al. (CoRR, 2023)

Learn-Morph-Infer: A new way of solving the inverse problem for brain tumor modeling. - Ivan Ezhov; Kevin Scibilia; Katharina Franitza; Felix Steinbauer; Suprosanna Shit; Lucas Zimmer; Jana Lipková; Florian Kofler; Johannes C. Paetzold; Luca Canalini; Diana Waldmannstetter; Martin J. Menten; et al. (Medical Image Anal., 2023)

A Learnable Prior Improves Inverse Tumor Growth Modeling. - Jonas Weidner; Ivan Ezhov; Michal Balcerak; Marie-Christin Metz; Sergey Litvinov; Sebastian Kaltenbach; Leonhard F. Feiner; Laurin Lux; Florian Kofler; Jana Lipková; Jonas Latz; Daniel Rueckert; et al. (IEEE Trans. Medical Imaging, 2025)