| Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ... arXiv preprint arXiv:1811.02629, 2018 | 1764 | 2018 |
| preCICE–a fully parallel library for multi-physics surface coupling HJ Bungartz, F Lindner, B Gatzhammer, M Mehl, K Scheufele, A Shukaev, ... Computers & Fluids 141, 250-258, 2016 | 334 | 2016 |
| Improving the performance of the partitioned QN-ILS procedure for fluid–structure interaction problems: Filtering R Haelterman, AEJ Bogaers, K Scheufele, B Uekermann, M Mehl Computers & Structures 171, 9-17, 2016 | 60 | 2016 |
| A comparison of various quasi-Newton schemes for partitioned fluid-structure interaction F Lindner, M Mehl, K Scheufele, B Uekermann Coupled VI: Proceedings of the VI International Conference on Computational …, 2015 | 46 | 2015 |
| Where did the tumor start? An inverse solver with sparse localization for tumor growth models S Subramanian, K Scheufele, M Mehl, G Biros Inverse problems 36 (4), 045006, 2020 | 34 | 2020 |
| Coupling brain-tumor biophysical models and diffeomorphic image registration K Scheufele, A Mang, A Gholami, C Davatzikos, G Biros, M Mehl Computer methods in applied mechanics and engineering 347, 533-567, 2019 | 33 | 2019 |
| Robust Multisecant Quasi-Newton Variants for Parallel Fluid-Structure Simulations---and Other Multiphysics Applications K Scheufele, M Mehl SIAM Journal on Scientific Computing 39 (5), S404-S433, 2017 | 28 | 2017 |
| Fully automatic calibration of tumor-growth models using a single mpMRI scan K Scheufele, S Subramanian, G Biros IEEE transactions on medical imaging 40 (1), 193-204, 2020 | 23 | 2020 |
| Multiatlas calibration of biophysical brain tumor growth models with mass effect S Subramanian, K Scheufele, N Himthani, G Biros Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 22 | 2020 |
| Partitioned fluid–structure–acoustics interaction on distributed data: Coupling via preCICE HJ Bungartz, F Lindner, M Mehl, K Scheufele, A Shukaev, B Uekermann Software for Exascale Computing-SPPEXA 2013-2015, 239-266, 2016 | 22 | 2016 |
| A framework for scalable biophysics-based image analysis A Gholami, A Mang, K Scheufele, C Davatzikos, M Mehl, G Biros Proceedings of the International Conference for High Performance Computing …, 2017 | 21 | 2017 |
| Image-driven biophysical tumor growth model calibration K Scheufele, S Subramanian, A Mang, G Biros, M Mehl SIAM journal on scientific computing: a publication of the Society for …, 2020 | 15 | 2020 |
| Robust quasi-newton methods for partitioned fluid-structure simulations K Scheufele | 11 | 2015 |
| Coupling schemes and inexact Newton for multi-physics and coupled optimization problems K Scheufele | 10 | 2018 |
| SIBIA-GlS: Scalable biophysics-based image analysis for glioma segmentation A Mang, S Tharakan, A Gholami, N Nimthani, S Subramanian, J Levitt, ... Proc BraTS 2017 Workshop, 197-204, 2017 | 10 | 2017 |
| A review on fast quasi-newton and accelerated fixed-point iterations for partitioned fluid–structure interaction simulation D Blom, F Lindner, M Mehl, K Scheufele, B Uekermann, A van Zuijlen Advances in Computational Fluid-Structure Interaction and Flow Simulation …, 2016 | 9 | 2016 |
| Ensemble inversion for brain tumor growth models with mass effect S Subramanian, A Ghafouri, KM Scheufele, N Himthani, C Davatzikos, ... IEEE Transactions on Medical Imaging 42 (4), 982-995, 2022 | 8 | 2022 |
| Calibration of Biophysical Models for tau-Protein Spreading in Alzheimer's Disease from PET-MRI K Scheufele, S Subramanian, G Biros arXiv preprint arXiv:2007.01236, 2020 | 3 | 2020 |
| Robust Quasi-Newton Methods for Partitioned FSI Simulations K Scheufele, M Mehl, F Lindner, B Uekermann WCCM, 2016 | 2 | 2016 |
| Additional results for the article:“Improving the performance of the partitioned QN-ILS procedure for fluid-structure interaction problems: filtering” R Haelterman, A Bogaers, B Uekermann, K Scheufele, M Mehl Available as Appendix A, 0 | 2 | |
