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Modelling temporal stability of EPI time series using magnitude images acquired with multi-channel receiver coils (2012)

by C Hutton, E Balteau, A Lutti, O Josephs, N Weiskopf
Venue:PLoS ONE
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by N. Boubela, Klaudius Kalcher, Christian Nasel, Ewald Moser, Jürgen R. Reichenbach, Vincent Keereman Ghent, Martin Krämer , 2014
"... Scanning fast and slow: current limitations of 3 Tesla ..."
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Scanning fast and slow: current limitations of 3 Tesla

SOFTWARE ORIGINAL ARTICLE POAS4SPM: AToolbox for SPM to Denoise Diffusion MRI Data

by Karsten Tabelow, Siawoosh Mohammadi, Nikolaus Weiskopf, Jörg Polzehl , 2014
"... # The Author(s) 2014. This article is published with open access at Springerlink.com Abstract We present an implementation of a recently devel-oped noise reduction algorithm for dMRI data, called multi-shell position orientation adaptive smoothing (msPOAS), as a toolbox for SPM. The method intrinsic ..."
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# The Author(s) 2014. This article is published with open access at Springerlink.com Abstract We present an implementation of a recently devel-oped noise reduction algorithm for dMRI data, called multi-shell position orientation adaptive smoothing (msPOAS), as a toolbox for SPM. The method intrinsically adapts to the structures of different size and shape in dMRI and hence avoids blurring typically observed in non-adaptive smoothing. We give examples for the usage of the toolbox and explain the determination of experiment-dependent parameters for an op-timal performance of msPOAS.
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... lead to larger estimates for σ, than the diffusion weighted volumes. Note, that the method of Constantinides et al. (1997) does not account for noise correlation due to multi-channel receiver coils (=-=Hutton et al. 2012-=-). Furthermore, non-background structure like ghosts within the defined background mask also leads to overestimates of σ. For msPOAS it is advisable to use a conservative small estimate for σ and pote...

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