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
  5. Wu Fung S, Ruthotto L: A Multiscale Method for Model Order Reduction in PDE Parameter Estimation, arXiv:1707.07598 [math.NA] 2017

Journal Articles

  1. 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
  2. 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
  3. 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
  4. Haber E, Ruthotto L: Stable Architectures for Deep Neural Networks, Inverse Problems, 34(1) 2017
  5. 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
  6. 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
  7. 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
  8. 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
  9. Ruthotto L, Greif C, Modersitzki J: A Stabilized Multigrid Solver for Hyperelastic Image Registration, Numerical Linear Algebra with Applications 2017 code
  10. Chung J, Ruthotto L: Computational methods for image reconstruction , NMR in Biomedicine 2016
  11. 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
  12. 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
  13. Fohring J, Haber E, Ruthotto L: Geophysical Imaging of Fluid Flow in Porous Media, SIAM Journal on Scientific Computing, 36(5), S218-S236, 2014
  14. Burger M, Modersitzki J, Ruthotto L: A Hyperelastic Regularization Energy for Image Registration, SIAM Journal on Scientific Computing, 35(1), B132-B148, 2013
  15. 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
  16. 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