Professoren und Lehrkräfte

Teaching

• Linear Algebra for Mathematicians
• Optimization for Mathematicians
  
• Mathematics for Electrical Engineering
  
• Mathematics for Mechanical Engineering
  

Lab

Lab for Mathematical Methods in Computer Vision and Machine Learning

Publications

Recent Publications

• L. Kiefer, M. Storath, A. Weinmann. Iterative Potts minimization for the recovery of signals with discontinuities from indirect measurements -- the multivariate case. Foundations of Computational Mathematics, 2020
  
• M. Storath, A. Weinmann. Variational regularization of inverse problems for manifold-valued data. Information and Inference: A Journal of the IMA, to appear
  
• M. Storath, A. Weinmann. Wavelet sparse regularization for manifold-valued data. Multiscale Modeling and Simulation: A SIAM Interdisciplinary Journal, 18(2):674–706, 2020
  
• L. Kiefer, M. Storath, A. Weinmann. An efficient algorithm for the piecewise affine-linear Mumford-Shah model based on a Taylor jet splitting. IEEE Transactions on Image Processing, 29:921–933, 2019
• M. Storath, L. Kiefer, A. Weinmann. Smoothing for signals with discontinuities using higher order Mumford-Shah models. Numerische Mathematik, 143(2):423-460, 2019
• M. Esposito, C. Hennersperger, R. Göbl, L. Demaret, M. Storath, N. Navab, M. Baust, A. Weinmann. Total variation regularization of pose signals with an application to 3D freehand ultrasound. IEEE Transactions on Medical Imaging, 38(10):2245–2258, 2019
• A. Bendinger, C. Debus, C. Glowa, C. Karger, J. Peter, M. Storath. Bolus arrival time estimation in dynamic contrast-enhanced MRI of small animals based on spline models. Physics in Medicine and Biology, 64(4):045003, 2019
• D. Fortun, M. Storath, D. Rickert, A. Weinmann, M. Unser. Fast piecewise-affine motion estimation without segmentation. IEEE Transactions on Image Processing, 27(11):5612–5624, 2018
• L. Kiefer, S. Petra, M. Storath, A. Weinmann. Direct MRI segmentation from k-space data by iterative Potts minimization. International Conference on Scale Space and Variational Methods (SSVM), 2019
• M. Weiler, F. Hamprecht, M. Storath. Learning steerable filters for rotation equivariant CNNs. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 849–858, 2018
  
• K. Bredies, M. Holler, M. Storath, A. Weinmann. Total generalized variation for manifold-valued data. SIAM Journal on Imaging Sciences, 11(3):1785–1848, 2018
• W. Erb, A. Weinmann, M. Ahlborg, C. Brandt, G. Bringout, T. Buzug, J. Frikel, C. Kaethner, T. Knopp, T. März, M. Möddel, M. Storath, A. Weber. Mathematical Analysis of the 1D Model and Reconstruction Schemes for Magnetic Particle Imaging. Inverse Problems, 34(5):055012, 2018
• M. Kiechle, M. Storath, A. Weinmann, M. Kleinsteuber. Model-based learning of local image features for unsupervised texture segmentation. IEEE Transactions on Image Processing, 27(4):1994–2007, 2018
• M. Storath, A. Weinmann. Fast median filtering for phase or orientation data. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(3):639–652, 2018
  

Full list here: Google Scholar

Open Source Software

• Pottslab - Multilabel image segmentation (color/gray/multichannel) based on the Potts model (aka piecewise constant Mumford-Shah model)
• DCEBE - Estimation of bolus arrival times for DCE-MRI signals
• CircleMedianFilter - Fast median filter for circle-valued data, for example signals or images describing phase or orientation
• L1TV - Denoising/reconstruction of piecewise constant signals using the L1TV model
  
• MumfordShah2D - Algorithms for edge preserving smoothing based on the Mumford-Shah model
• PALMS Image Partitioning - A New Parallel Algorithm for the Piecewise Affine-Linear Mumford-Shah Model
  

Links

Brücken schlagen: Von der Schulmathematik zur Hochschulmathematik