J. Polzehl

发表

Exploratory Projection Pursuit

S. Klinke, J. Polzehl, 1995 .

Structure adaptive approach for dimension reduction

J. Polzehl, V. Spokoiny, M. Hristache, 2001 .

Image denoising: Pointwise adaptive approach

J. Polzehl, V. Spokoiny, 2003 .

Propagation-Separation Approach for Local Likelihood Estimation

J. Polzehl, V. Spokoiny, 2006 .

Structure Adaptive Approach for Dimension Reduction 1

A. Juditsky, J. Polzehl, V. Spokoiny, 2001 .

On bandwidth choice in nonparametric regression with both short- and long-range dependent errors

S. Lahiri, P. Hall, J. Polzehl, 1995 .

Low SNR in Diffusion MRI Models

Karsten Tabelow, Jörg Polzehl, J. Polzehl, 2016 .

Local likelihood modeling by adaptive weights smoothing

J. Polzehl, V. Spokoiny, 2004 .

Beyond the diffusion tensor model: The package dti

J. Polzehl, K. Tabelow, 2010 .

Structural Adaptive Smoothing Procedures

J. Polzehl, R. Dahlhaus, P. Mrázek, 2008 .

Functional MRI of the zebra finch brain during song stimulation suggests a lateralized response topography

J. Polzehl, O. Tchernichovski, H. Voss, 2007, Proceedings of the National Academy of Sciences.

Bias corrected bootstrap bandwidth selection

Jörg Polzehl, Birgit Grund, J. Polzehl, 1997 .

Varying coefficient regression modeling by adaptive weights smoothing

Jörg Polzehl, Vladimir Spokoiny, J. Polzehl, 2003 .

Assimilation of magnetic resonance elastography data in an in silico brain model

J. Polzehl, I. Sack, A. Caiazzo, 2022, ArXiv.

F 2 Image processing

J. Polzehl, H. Hege, H. Lamecker, 2016 .

Structural Adaptive Smoothing by Propagation–Separation Methods

J. Polzehl, V. Spokoiny, 2008 .

Exploratory Projection Pursuit

S. Klinke, J. Polzehl, 1995 .

Model Selection and Variable Transformations in Nonlinear Regression

J. Polzehl, O. Bunke, B. Droge, 1993 .

High-resolution diffusion kurtosis imaging at 3T enabled by advanced post-processing

Nikolaus Weiskopf, Thorsten Feiweier, Karsten Tabelow, 2015, Front. Neurosci..

Ground reaction forces and external hip joint moments predict in vivo hip contact forces during gait.

Sónia A. Alves, J. Polzehl, G. Duda, 2022, Journal of biomechanics.

Assimilation of magnetic resonance elastography data in an in silico brain model

J. Polzehl, I. Sack, A. Caiazzo, 2022, ArXiv.

On a symmetrized simulation extrapolation estimator in linear errors-in-variables models

Silvelyn Zwanzig, Jörg Polzehl, J. Polzehl, 2004, Comput. Stat. Data Anal..

Splus Tools for Model Selection in Nonlinear Regression

J. Polzehl, O. Bunke, B. Droge, 1998 .

Local estimation of the noise level in MRI using structural adaptation

Karsten Tabelow, Jörg Polzehl, Henning U. Voss, 2014, Medical Image Anal..

Adaptive smoothing of multi-shell diffusion weighted magnetic resonance data by msPOAS

Nikolaus Weiskopf, Karsten Tabelow, Jörg Polzehl, 2014, NeuroImage.

POAS4SPM: A Toolbox for SPM to Denoise Diffusion MRI Data

Nikolaus Weiskopf, Karsten Tabelow, Jörg Polzehl, 2014, Neuroinformatics.

Structural Adaptive Smoothing: Principles and Applications in Imaging

Karsten Tabelow, Jörg Polzehl, J. Polzehl, 2012, Mathematical Methods for Signal and Image Analysis and Representation.

Beyond the Gaussian Model in Diffusion-Weighted Imaging: The Package dti

Karsten Tabelow, Jörg Polzehl, J. Polzehl, 2011 .

Image analysis and statistical inference in neuroimaging with R

Karsten Tabelow, Jörg Polzehl, Volker J. Schmid, 2011, NeuroImage.

Structural Adaptive Smoothing in Diffusion Tensor Imaging: The R Package dti

Karsten Tabelow, Jörg Polzehl, J. Polzehl, 2009 .

Diffusion tensor imaging: Structural adaptive smoothing

Karsten Tabelow, Jörg Polzehl, Henning U. Voss, 2008, NeuroImage.

Structural adaptive segmentation for statistical parametric mapping

Karsten Tabelow, Jörg Polzehl, Henning U. Voss, 2010, NeuroImage.

Model Selection, Transformations and Variance Estimation in Nonlinear Regression

Jörg Polzehl, Bernd Droge, Olaf Bunke, 1999 .

Experiences with Bivariate Projection Pursuit Indices

S. Klinke, J. Polzehl, org Polzehl, 1995 .

Projection pursuit discriminant analysis

Jörg Polzehl, J. Polzehl, 1995 .

Displacement and Pressure Reconstruction from Magnetic Resonance Elastography Images: Application to an In Silico Brain Model

J. Polzehl, I. Sack, A. Caiazzo, 2022, SIAM J. Imaging Sci..

Position-orientation adaptive smoothing of diffusion weighted magnetic resonance data (POAS)

Alfred Anwander, Karsten Tabelow, Robin M. Heidemann, 2012, Medical Image Anal..

Analyzing fMRI experiments with structural adaptive smoothing procedures

Karsten Tabelow, Jörg Polzehl, Henning U. Voss, 2006, NeuroImage.

High-resolution fMRI: Overcoming the signal-to-noise problem

Karsten Tabelow, Jörg Polzehl, Henning U. Voss, 2009, Journal of Neuroscience Methods.

Improving Accuracy and Temporal Resolution of Learning Curve Estimation for within- and across-Session Analysis

Karsten Tabelow, Jörg Polzehl, Reinhard König, 2015, PloS one.

Adaptive Smoothing of Digital Images: The R Package adimpro

Karsten Tabelow, Jörg Polzehl, J. Polzehl, 2007 .

Functional and dynamic magnetic resonance imaging using vector adaptive weights smoothing

Jörg Polzehl, Vladimir Spokoiny, J. Polzehl, 2001 .

Using jackknife in nonlinear models - confidence regions for a function of the structural parameter

J. Polzehl, 1985 .

A propagation-separation approach to estimate the autocorrelation in a time-series

J. Polzehl, F. Godtliebsen, D. Divine, 2008 .

Simultaneous bootstrap confidence bands in nonparametric regression

Jörg Polzehl, Michael H. Neumann, J. Polzehl, 1998 .

Adaptive weights smoothing with applications to image restoration

J. Polzehl, V. Spokoiny, J. Polzehl, 1998 .

On a comparison of different simulation extrapolation estimators in linear errors-in-variables models

J. Polzehl, S. Zwanzig, 2003 .

Statistical Parametric Maps for Functional MRI Experiments in R: The Package fmri

Karsten Tabelow, Jörg Polzehl, J. Polzehl, 2011 .

Analysing fMRI experiments with the fmri package in R. Version 1.0 - A users guide.

Karsten Tabelow, Jörg Polzehl, J. Polzehl, 2006 .

Modeling the orientation distribution function by mixtures of angular central Gaussian distributions

K. Tabelow, H. U. Voss, J. Polzehl, 2012, Journal of Neuroscience Methods.