POAS4SPM: A Toolbox for SPM to Denoise Diffusion MRI Data

We present an implementation of a recently developed 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 typ...

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Detalles Bibliográficos
Autores principales: Tabelow, Karsten, Mohammadi, Siawoosh, Weiskopf, Nikolaus, Polzehl, Jörg
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2014
Materias:
Software Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4303737/
https://www.ncbi.nlm.nih.gov/pubmed/24993814
http://dx.doi.org/10.1007/s12021-014-9228-3
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author Tabelow, Karsten
Mohammadi, Siawoosh
Weiskopf, Nikolaus
Polzehl, Jörg
author_facet Tabelow, Karsten
Mohammadi, Siawoosh
Weiskopf, Nikolaus
Polzehl, Jörg
author_sort Tabelow, Karsten
collection PubMed
description We present an implementation of a recently developed 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 optimal performance of msPOAS.
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spelling pubmed-43037372015-01-27 POAS4SPM: A Toolbox for SPM to Denoise Diffusion MRI Data Tabelow, Karsten Mohammadi, Siawoosh Weiskopf, Nikolaus Polzehl, Jörg Neuroinformatics Software Original Article We present an implementation of a recently developed 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 optimal performance of msPOAS. Springer US 2014-07-05 2015 /pmc/articles/PMC4303737/ /pubmed/24993814 http://dx.doi.org/10.1007/s12021-014-9228-3 Text en © The Author(s) 2014 https://creativecommons.org/licenses/by/4.0/ Open AccessThis article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
spellingShingle Software Original Article
Tabelow, Karsten
Mohammadi, Siawoosh
Weiskopf, Nikolaus
Polzehl, Jörg
POAS4SPM: A Toolbox for SPM to Denoise Diffusion MRI Data
title POAS4SPM: A Toolbox for SPM to Denoise Diffusion MRI Data
title_full POAS4SPM: A Toolbox for SPM to Denoise Diffusion MRI Data
title_fullStr POAS4SPM: A Toolbox for SPM to Denoise Diffusion MRI Data
title_full_unstemmed POAS4SPM: A Toolbox for SPM to Denoise Diffusion MRI Data
title_short POAS4SPM: A Toolbox for SPM to Denoise Diffusion MRI Data
title_sort poas4spm: a toolbox for spm to denoise diffusion mri data
topic Software Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4303737/
https://www.ncbi.nlm.nih.gov/pubmed/24993814
http://dx.doi.org/10.1007/s12021-014-9228-3
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AT weiskopfnikolaus poas4spmatoolboxforspmtodenoisediffusionmridata
AT polzehljorg poas4spmatoolboxforspmtodenoisediffusionmridata

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