Lars Ruthotto


Below is a selection of my work. Find me also onGoogle Scholar and ResearchGate, Twitter.

Book Chapter

  1. Ruthotto L, Modersitzki J: Non-linear Image Registration , Handbook of Mathematical Methods in Imaging (edited by Otmar Scherzer), 2005-2051, 2015

Submitted Articles

  1. Wu Fung S, Ruthotto L: An Uncertainty-Weighted Asynchronous ADMM Method for Parallel PDE Parameter Estimation, arXiv:1806.00192 [math.NA] 2018
  2. Treister E, Ruthotto L, Sharoni M, Zafrani S, Haber E: Low-Cost Parameterizations of Deep Convolution Neural Networks arXiv:1805.07821 [math.NA] 2018
  3. Haber E, Lucka F, Ruthotto L: Never look back - The EnKF method and its application to the training of neural networks without back propagation arXiv:1805.08034 [math.NA] 2018
  4. Ruthotto L, Haber E: Deep Neural Networks motivated by Partial Differential Equations, arXiv:1804.04272 [cs.LG] 2018

Journal Articles

  1. Wu Fung S, Ruthotto L: A Multiscale Method for Model Order Reduction in PDE Parameter Estimation, Journal of Computational and Applied Mathematics accepted, Sep. 2018
  2. Mustonen L, Gao X, Santana A, Mitchell R, Vigfusson Y, Ruthotto L : A Bayesian framework for molecular strain identification from mixed diagnostic samples, Inverse Problems 34(10), 2018
  3. Herring JL, Nagy JG, Ruthotto L: LAP: a Linearize and Project Method for Solving Inverse Problems with Coupled Variables, STSIP Special Issue on Harmonic Analysis and Inverse Problems 2018
  4. Ruthotto L, Chung J, Chung M: Optimal Experimental Design for Inverse Problems with State Contraints, SIAM Journal on Scientific Computing, 40(4), B1080--B1100 2018
  5. Haber E, Ruthotto L: Stable Architectures for Deep Neural Networks, Inverse Problems, 34(1) 2017
  6. Lin C Y, Veneziani A, Ruthotto L: Numerical Methods for Polyline-to-Point-Cloud Registration with Applications to Patient-Specific Stent Reconstruction, International Journal for Numerical Methods in Biomedical Engineering, 34(3) 2017
  7. Macdonald J, Ruthotto L: Improved Susceptibility Artifact Correction of Echo Planar MRI using the Alternating Direction Method of Multipliers, Journal of Mathematical Imaging and Vision, pp 1-15 2017 preprint
  8. Mang A, Ruthotto L: A Lagrangian Gauss-Newton-Krylov Solver for Mass- and Intensity-Preserving Diffeomorphic Image Registration, SIAM Journal on Scientific Computing, 39(5), B5860-B5885 2017 code
  9. Ruthotto L, Treister E, Haber E: jInv - a flexible Julia package for PDE parameter estimation, SIAM Journal on Scientific Computing, 39(5), S702-S722 2017
  10. Ruthotto L, Greif C, Modersitzki J: A Stabilized Multigrid Solver for Hyperelastic Image Registration, Numerical Linear Algebra with Applications 2017 code
  11. Chung J, Ruthotto L: Computational methods for image reconstruction , NMR in Biomedicine 2016
  12. Mohammadi S, Tabelow K, Ruthotto L, Feiweier T, Polzehl J, Weiskopf N: High-resolution Diffusion Kurtosis Imaging at 3T Enabled by Advanced Post-Processing , Frontiers in Neuroscience, 8, 2014
  13. Haber E and Ruthotto L: A Multiscale Finite Volume Method for Maxwell's Equations at Low Frequencies, Geophysical Journal International, 199(2):1268-1277, 2014
  14. Fohring J, Haber E, Ruthotto L: Geophysical Imaging of Fluid Flow in Porous Media, SIAM Journal on Scientific Computing, 36(5), S218-S236, 2014
  15. Burger M, Modersitzki J, Ruthotto L: A Hyperelastic Regularization Energy for Image Registration, SIAM Journal on Scientific Computing, 35(1), B132-B148, 2013
  16. Ruthotto L, Kugel H, Olesch J, Fischer B, Modersitzki J, Burger M, Wolters CH: Diffeomorphic Susceptibility Artifact Correction of Diffusion-weighted Magnetic Resonance Images, Physics in Medicine and Biology, 57(18), 5715-5731, 2012
  17. Gigengack F, Ruthotto L, Burger M, Wolters CH, Jiang X, Schäfers KP: Motion Correction in Dual Gated Cardiac PET using Mass-preserving Image Registration, IEEE Transactions on Medical Imaging, 31(3), 698-712, 2012

Selected Peer-Reviewed Conference Proceedings

  1. Chang B, Meng L, Haber E, Ruthotto L, Begert D, Holtham E: Reversible Architectures for Arbitrarily Deep Residual Neural Networks, AAAI Conference on Artificial Intelligence 2018
  2. Haber E, Ruthotto L, Holtham E, Jun SH: Learning across scales - A multiscale method for Convolution Neural Networks, AAAI Conference on Artificial Intelligence 2017
  3. März M, Ruthotto L: Combined Background Field Removal and Reconstruction for Quantitative Susceptibility Mapping, Bildverarbeitung für die Medizin, 8-13, 2016
  4. Ruthotto L, Mohammadi S, Weiskopf N: A New Method for Joint Susceptibility Artefact Correction and Super-resolution for dMRI, SPIE Medical Imaging, 90340P-5, 2014
  5. Heck C, Ruthotto L, Modersitzki J, Berkels B: Model-Based Parameter-Estimation in DCE-MRI Without an Aterial Input Function, Bildverarbeitung für die Medizin, 246-251, 2014
  6. Ruthotto L, Mohammadi, S, Heck C, Modersitzki J, Weiskopf N: Hyperelastic Susceptibility Artifact Correction of DTI in SPM, Bildverarbeitung für die Medizin, 344-349, 2013
  7. Ruthotto L, Hodneland, E, Modersitzki J: Registration of Dynamic Contrast Enhanced MRI with Local Rigidity Constraints, WBIR'12 Proc. of the 5th International Conference on Biomedical Image Registration, 190-198, 2012
  8. Ruthotto L, Gigengack F, Burger M, Wolters CH, Jiang C, Schäfers KP, Modersitzki J: A Simplified Pipeline for Motion Correction in Dual Gated Cardiac PET, Bildverarbeitung für die Medizin, 51-59, 2012
  9. Olesch J, Ruthotto L, Kugel H, Skare S, Fischer B, Wolters CH: A Variational Approach for the Correction of Field-inhomogeneities in EPI Sequences, SPIE Medical Imaging, 76230K-8, 2010