Veröffentlichungen

The impact of model assumptions in scalar-on-image regression

Complex statistical models such as scalar-on-image regression often require strong assumptions to overcome the issue of …

Regionale Haeufigkeit von revaskularisierenden Prozeduren bei Karotisstenose in Deutschland

For Germany, regional variation of procedure rates of carotid endarterectomy (CEA) and carotid artery stenting (CAS) performed for …

Bivariate spatiotemporal disease mapping of cancer of the breast and cervix uteri among Iranian women

Cervical cancer in women is one of the most common cancers and breast cancer has grown dramatically in recent years. The purpose of …

Quantitative analyses of the 3D nuclear landscape recorded with super-resolved fluorescence microscopy

Recent advancements of super-resolved fluorescence microscopy have revolutionized microscopic studies of cells, including the …

Fitting large-scale structured additive regression models

Fitting regression models can be challenging when regression coefficients are high-dimensional. Especially when large spatial or …

Stage-dependent remodeling of the nuclear envelope and lamina during rabbit early embryonic development

Utilizing 3D structured illumination microscopy, we investigated the quality and quantity of nuclear invaginations and the distribution …

Boosting in Nonlinear Regression Models with an Application to DCE-MRI Data

For the statistical analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data, compartment models are a commonly …

Spatially regularized estimation for the analysis of dynamic contrast-enhanced magnetic resonance imaging data

Competing compartment models of different complexities have been used for the quantitative analysis of dynamic contrast-enhanced …

Trends of breast cancer incidence in Iran during 2004-2008: A bayesian space-time model

Background: Breast cancer is the most frequently diagnosed cancer in women and estimating its relative risks and trends of incidence at …

Spatial two-tissue compartment model for dynamic contrast-enhanced magnetic resonance imaging

In the quantitative analysis of dynamic contrast-enhanced magnetic resonance imaging compartment models allow the uptake of contrast …

Sensitivity to Prior Specification in Bayesian Genome-based Prediction Models

Different statistical models have been proposed for maximizing prediction accuracy in genome-based prediction of breeding values in …

Working with the DICOM and NIfTI Data Standards in R

Two packages, oro.dicom and oro.nifti, are provided for the interaction with and manipulation of medical imaging data that conform to …

Voxel-based adaptive spatio-temporal modelling of perfusion cardiovascular MRI.

Contrast enhanced myocardial perfusion magnetic resonance imaging (MRI) is a promising technique, providing insight into how reduced …

Quantitative Analysis of Dynamic Contrast-Enhanced and Diffusion-Weighted Magnetic Resonance Imaging for Oncology in R

The package dcemriS4 provides a complete set of data analysis tools for quantitative assessment of dynamic contrast-enhanced magnetic …

Multivariate Disease Mapping of Seven Prevalent Cancers in Iran using a Shared Component Model.

Background: The aim of this study was to model the geographical variation in incidence and risk factors of seven prevalent cancers in …

Image analysis and statistical inference in neuroimaging with R

R is a language and environment for statistical computing and graphics. It can be considered an alternative implementation of the S …

Bayesian space-time analysis of Echinococcus multilocularis-infections in foxes.

A total of 26,220 foxes that were hunted or found dead in Thuringia, Germany, between 1990 and 2009 were examined for infection with …

Two Tissue Compartment Model in DCE-MRI: A Bayesian Approach

In this paper, we propose a compartment model with two interstitial space compartments for the quantitative description of the contrast …

Spatio-Temporal Modelling of First-Pass Perfusion Cardiovascular MRI

Myocardial perfusion MRI provides valuable insight into how coronary artery and microvascular diseases affect myocardial tissue. …

Attenuation Resilient AIF Estimation Based on Hierarchical Bayesian Modelling for First Pass Myocardial Perfusion MRI

Non-linear attenuation of the Arterial Input Function (AIF) is a major problem in first-pass MR perfusion imaging due to the high …

Semi-parametric analysis of dynamic contrast-enhanced MRI using Bayesian P-splines

Current approaches to quantitative analysis of DCE-MRI with non-linear models involve the convolution of an arterial input function …

A two-component model for counts of infectious diseases.

We propose a stochastic model for the analysis of time series of disease counts as collected in typical surveillance systems on …

Statistical analysis of pharmacokinetic models in dynamic contrast-enhanced magnetic resonance imaging.

This paper assesses the estimation of kinetic parameters from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). …

Bayesian Extrapolation of Space–Time Trends in Cancer Registry Data

We apply a full Bayesian model framework to a dataset on stomach cancer mortality in West Germany. The data are stratified by age …

A Bayesian model for spatial wildlife disease prevalence data

The analysis of the geographical distribution of disease on the scale of geographic areas such as administrative boundaries plays an …