Zobrazeno 1 - 10
of 57
pro vyhledávání: '"Karsten Tabelow"'
Autor:
Siawoosh Mohammadi, Tobias Streubel, Leonie Klock, Luke J. Edwards, Antoine Lutti, Kerrin J. Pine, Sandra Weber, Patrick Scheibe, Gabriel Ziegler, Jürgen Gallinat, Simone Kühn, Martina F. Callaghan, Nikolaus Weiskopf, Karsten Tabelow
Publikováno v:
NeuroImage, Vol 262, Iss , Pp 119529- (2022)
Multi-Parameter Mapping (MPM) is a comprehensive quantitative neuroimaging protocol that enables estimation of four physical parameters (longitudinal and effective transverse relaxation rates R1 and R2*, proton density PD, and magnetization transfer
Externí odkaz:
https://doaj.org/article/a413d32925064f17897fdfa222e184e3
Publikováno v:
Journal of Statistical Software, Vol 95, Iss 1, Pp 1-27 (2020)
Image reconstruction from noisy data has a long history of methodological development and is based on a variety of ideas. In this paper we introduce a new method called patchwise adaptive smoothing, that extends the propagation-separation approach by
Externí odkaz:
https://doaj.org/article/7a483777ae794754a4e3acfc811411b6
Autor:
Martina F. Callaghan, Antoine Lutti, John Ashburner, Evelyne Balteau, Nadège Corbin, Bogdan Draganski, Gunther Helms, Ferath Kherif, Tobias Leutritz, Siawoosh Mohammadi, Christophe Phillips, Enrico Reimer, Lars Ruthotto, Maryam Seif, Karsten Tabelow, Gabriel Ziegler, Nikolaus Weiskopf
Publikováno v:
Data in Brief, Vol 25, Iss , Pp - (2019)
The hMRI toolbox is an open-source toolbox for the calculation of quantitative MRI parameter maps from a series of weighted imaging data, and optionally additional calibration data. The multi-parameter mapping (MPM) protocol, incorporating calibratio
Externí odkaz:
https://doaj.org/article/a1980d187cb84cd2ba82c9803e7f1ff7
Publikováno v:
PLoS ONE, Vol 11, Iss 2, p e0149016 (2016)
Signal detection in functional magnetic resonance imaging (fMRI) inherently involves the problem of testing a large number of hypotheses. A popular strategy to address this multiplicity is the control of the false discovery rate (FDR). In this work w
Externí odkaz:
https://doaj.org/article/48ea1a3968a64719bd1a1edf536b7ec8
Publikováno v:
PLoS ONE, Vol 11, Iss 6, p e0157355 (2016)
Estimation of learning curves is ubiquitously based on proportions of correct responses within moving trial windows. Thereby, it is tacitly assumed that learning performance is constant within the moving windows, which, however, is often not the case
Externí odkaz:
https://doaj.org/article/0003a2ce47674a04adea1a32963d23f7
Autor:
Karsten Tabelow, Jörg Polzehl
Publikováno v:
Journal of Statistical Software, Vol 44, Iss 12 (2011)
Diffusion weighted imaging (DWI) is a magnetic resonance (MR) based method to investigate water diffusion in tissue like the human brain. Inference focuses on integral properties of the tissue microstructure. The acquired data are usually modeled usi
Externí odkaz:
https://doaj.org/article/d25e9a64f7dd4949b213c1597c6fcae2
Autor:
Brandon Whitcher, Karsten Tabelow
Publikováno v:
Journal of Statistical Software, Vol 44, Iss 01 (2011)
The special volume on “Magnetic Resonance Imaging in R” features articles and packages related to a variety of imaging modalities: functional MRI, diffusion-weighted MRI, dynamic contrast-enhanced MRI, dynamic susceptibility-contrast MRI and stru
Externí odkaz:
https://doaj.org/article/5aa6edca850546249203e84e48e904bb
Autor:
Jörg Polzehl, Karsten Tabelow
Publikováno v:
Journal of Statistical Software, Vol 44, Iss 11 (2011)
The purpose of the package fmri is the analysis of single subject functional magnetic resonance imaging (fMRI) data. It provides fMRI analysis from time series modeling by a linear model to signal detection and publication quality images. Specificall
Externí odkaz:
https://doaj.org/article/a7c3c61e9d7048299cd0c7fcc6356ba5
Autor:
Jorg Polzehl, Karsten Tabelow
Publikováno v:
Journal of Statistical Software, Vol 31, Iss 09 (2009)
Diffusion weighted imaging has become and will certainly continue to be an important tool in medical research and diagnostics. Data obtained with diffusion weighted imaging are characterized by a high noise level. Thus, estimation of quantities like
Externí odkaz:
https://doaj.org/article/67549b4b5d0d4660ba82dff99c784164
Autor:
Jorg Polzehl, Karsten Tabelow
Publikováno v:
Journal of Statistical Software, Vol 19, Iss 1 (2007)
Digital imaging has become omnipresent in the past years with a bulk of applications ranging from medical imaging to photography. When pushing the limits of resolution and sensitivity noise has ever been a major issue. However, commonly used non-adap
Externí odkaz:
https://doaj.org/article/3a9028f9d62b43c0910d0576597462d3