Adaptive weights smoothing with applications to image restoration J Polzehl, VG Spokoiny Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2000 | 306 | 2000 |

Propagation-separation approach for local likelihood estimation J Polzehl, V Spokoiny Probability Theory and Related Fields 135, 335-362, 2006 | 250 | 2006 |

Structure adaptive approach for dimension reduction M Hristache, A Juditsky, J Polzehl, V Spokoiny Annals of Statistics, 1537-1566, 2001 | 229 | 2001 |

Simultaneous bootstrap confidence bands in nonparametric regression MH Neumann, J Polzehl Journal of Nonparametric Statistics 9 (4), 307-333, 1998 | 129 | 1998 |

On bandwidth choice in nonparametric regression with both short-and long-range dependent errors P Hall, SN Lahiri, J Polzehl The Annals of Statistics 23 (6), 1921-1936, 1995 | 112 | 1995 |

Functional MRI of the zebra finch brain during song stimulation suggests a lateralized response topography HU Voss, K Tabelow, J Polzehl, O Tchernichovski, KK Maul, ... Proceedings of the National Academy of Sciences 104 (25), 10667-10672, 2007 | 105 | 2007 |

Analyzing fMRI experiments with structural adaptive smoothing procedures K Tabelow, J Polzehl, HU Voss, V Spokoiny NeuroImage 33 (1), 55-62, 2006 | 105 | 2006 |

Diffusion tensor imaging: structural adaptive smoothing K Tabelow, J Polzehl, V Spokoiny, HU Voss NeuroImage 39 (4), 1763-1773, 2008 | 94 | 2008 |

Image denoising: pointwise adaptive approach J Polzehl, V Spokoiny The Annals of Statistics 31 (1), 30-57, 2003 | 77 | 2003 |

Position-orientation adaptive smoothing of diffusion weighted magnetic resonance data (POAS) SMA Becker, K Tabelow, HU Voss, A Anwander, RM Heidemann, ... Medical image analysis 16 (6), 1142-1155, 2012 | 69 | 2012 |

Local likelihood modeling by adaptive weights smoothing J Polzehl, V Spokoiny | 56 | 2004 |

Model selection, transformations and variance estimation in nonlinear regression O Bunke, B Droge, J Polzehl Statistics: A Journal of Theoretical and Applied Statistics 33 (3), 197-240, 1999 | 54* | 1999 |

Adaptive smoothing of multi-shell diffusion weighted magnetic resonance data by msPOAS SMA Becker, K Tabelow, S Mohammadi, N Weiskopf, J Polzehl Neuroimage 95, 90-105, 2014 | 51 | 2014 |

Adaptive smoothing of digital images: The R package adimpro J Polzehl, K Tabelow Los Angeles, Calif.: UCLA, Dept. of Statistics, 2007 | 47 | 2007 |

Statistical parametric maps for functional MRI experiments in R: The package fmri K Tabelow, J Polzehl Journal of Statistical Software 44, 1-21, 2011 | 44 | 2011 |

Projection pursuit discriminant analysis J Polzehl Computational statistics & data analysis 20 (2), 141-157, 1995 | 43 | 1995 |

Structural adaptive segmentation for statistical parametric mapping J Polzehl, HU Voss, K Tabelow NeuroImage 52 (2), 515-523, 2010 | 39 | 2010 |

High-resolution fMRI: Overcoming the signal-to-noise problem K Tabelow, V Piëch, J Polzehl, HU Voss Journal of Neuroscience Methods 178 (2), 357-365, 2009 | 39 | 2009 |

Image analysis and statistical inference in neuroimaging with R K Tabelow, JD Clayden, PL De Micheaux, J Polzehl, VJ Schmid, ... NeuroImage 55 (4), 1686-1693, 2011 | 38 | 2011 |

fmri: A Package for Analyzing fmri Data J Polzehl, K Tabelow RNews 7 (2), 13-17, 2007 | 34 | 2007 |