A parallel neural network approach to prediction of Parkinson’s Disease F Åström, R Koker Expert Systems with Applications 38 (10), 12470-12474, 2011 | 89 | 2011 |

Image labeling by assignment F Åström, S Petra, B Schmitzer, C Schnörr Journal of Mathematical Imaging and Vision 58 (2), 211-238, 2017 | 31 | 2017 |

On tensor-based PDEs and their corresponding variational formulations with application to color image denoising F Åström, G Baravdish, M Felsberg European Conference on Computer Vision, 215-228, 2012 | 13 | 2012 |

On Backward *p*(*x*)-Parabolic Equations for Image EnhancementG Baravdish, O Svensson, F Åström Numerical Functional Analysis and Optimization 36 (2), 147-168, 2015 | 11 | 2015 |

A tensor variational formulation of gradient energy total variation F Åström, G Baravdish, M Felsberg International Workshop on Energy Minimization Methods in Computer Vision and …, 2015 | 10 | 2015 |

Color persistent anisotropic diffusion of images F Åström, M Felsberg, R Lenz Scandinavian Conference on Image Analysis, 262-272, 2011 | 10 | 2011 |

Image labeling based on graphical models using Wasserstein messages and geometric assignment R Hühnerbein, F Savarino, F Åström, C Schnörr SIAM Journal on Imaging Sciences 11 (2), 1317-1362, 2018 | 9 | 2018 |

Targeted iterative filtering F Åström, M Felsberg, G Baravdish, C Lundström International Conference on Scale Space and Variational Methods in Computer …, 2013 | 6 | 2013 |

Numerical reconstruction of brain tumours R Jaroudi, G Baravdish, BT Johansson, F Åström Inverse Problems in Science and Engineering 27 (3), 278-298, 2019 | 5 | 2019 |

Unsupervised label learning on manifolds by spatially regularized geometric assignment A Zern, M Zisler, F Åström, S Petra, C Schnörr German Conference on Pattern Recognition, 698-713, 2018 | 5 | 2018 |

Numerical integration of Riemannian gradient flows for image labeling F Savarino, R Hühnerbein, F Åström, J Recknagel, C Schnörr International Conference on Scale Space and Variational Methods in Computer …, 2017 | 5 | 2017 |

Source localization of reaction-diffusion models for brain tumors R Jaroudi, G Baravdish, F Åström, BT Johansson German Conference on Pattern Recognition, 414-425, 2016 | 5 | 2016 |

Mapping-based image diffusion F Åström, M Felsberg, G Baravdish Journal of Mathematical Imaging and Vision 57 (3), 293-323, 2017 | 4 | 2017 |

On coupled regularization for non-convex variational image enhancement F Åström, C Schnorr 2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR), 786-790, 2015 | 4 | 2015 |

MAP image labeling using Wasserstein messages and geometric assignment F Åström, R Hühnerbein, F Savarino, J Recknagel, C Schnörr International Conference on Scale Space and Variational Methods in Computer …, 2017 | 3 | 2017 |

Color image regularization via channel mixing and half quadratic minimization F Åström 2016 IEEE International Conference on Image Processing (ICIP), 4007-4011, 2016 | 3 | 2016 |

Variational tensor-based models for image diffusion in non-linear domains F Åström Linköping University Electronic Press, 2015 | 3 | 2015 |

Image reconstruction by multilabel propagation M Zisler, F Åström, S Petra, C Schnörr International Conference on Scale Space and Variational Methods in Computer …, 2017 | 2 | 2017 |

Graphical model parameter learning by inverse linear programming V Trajkovska, P Swoboda, F Åström, S Petra International Conference on Scale Space and Variational Methods in Computer …, 2017 | 2 | 2017 |

A geometric approach to image labeling F Åström, S Petra, B Schmitzer, C Schnörr European Conference on Computer Vision, 139-154, 2016 | 2 | 2016 |