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dc.contributorVall d'Hebron Barcelona Hospital Campus
dc.contributor.authorMarschallinger, Robert
dc.contributor.authorTur Gomez, Carmen
dc.contributor.authorMarschallinger, Hannes
dc.contributor.authorSellner, Johann
dc.date.accessioned2021-06-16T11:14:05Z
dc.date.available2021-06-16T11:14:05Z
dc.date.issued2021-01-12
dc.identifier.citationMarschallinger R, Tur C, Marschallinger H, Sellner J. A R-Script for Generating Multiple Sclerosis Lesion Pattern Discrimination Plots. Brain Sci. 2021 Jan 12;11(1):90.
dc.identifier.issn2076-3425
dc.identifier.urihttp://hdl.handle.net/11351/6078
dc.descriptionR statistical computing; Geostatistics; Multiple sclerosis
dc.description.abstractOne significant characteristic of Multiple Sclerosis (MS), a chronic inflammatory demyelinating disease of the central nervous system, is the evolution of highly variable patterns of white matter lesions. Based on geostatistical metrics, the MS-Lesion Pattern Discrimination Plot reduces complex three- and four-dimensional configurations of MS-White Matter Lesions to a well-arranged and standardized two-dimensional plot that facilitates follow-up, cross-sectional and medication impact analysis. Here, we present a script that generates the MS-Lesion Pattern Discrimination Plot, using the widespread statistical computing environment R. Input data to the script are Nifti-1 or Analyze-7.5 files with individual MS-White Matter Lesion masks in Montreal Normal Brain geometry. The MS-Lesion Pattern Discrimination Plot, variogram plots and associated fitting statistics are output to the R console and exported to standard graphics and text files. Besides reviewing relevant geostatistical basics and commenting on implementation details for smooth customization and extension, the paper guides through generating MS-Lesion Pattern Discrimination Plots using publicly available synthetic MS-Lesion patterns. The paper is accompanied by the R script LDPgenerator.r, a small sample data set and associated graphics for comparison.
dc.language.isoeng
dc.publisherMDPI
dc.relation.ispartofseriesBrain Sciences;11(1)
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceScientia
dc.subjectEsclerosi múltiple
dc.subjectImatgeria per ressonància magnètica
dc.subjectPatrons de programari
dc.subject.meshMultiple Sclerosis
dc.subject.meshPattern Recognition, Automated
dc.subject.meshMagnetic Resonance Imaging
dc.titleA R-Script for Generating Multiple Sclerosis Lesion Pattern Discrimination Plots
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doi10.3390/brainsci11010090
dc.subject.decsesclerosis múltiple
dc.subject.decsreconocimiento automatizado de patrones
dc.subject.decsimagen por resonancia magnética
dc.relation.publishversionhttps://www.mdpi.com/2076-3425/11/1/90
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dc.audienceProfessionals
dc.contributor.organismesInstitut Català de la Salut
dc.contributor.authoraffiliation[Marschallinger R] Department of Geoinformatics, University of Salzburg, Salzburg, Austria. Department of Neurology, Christian Doppler Medical Center, Paracelsus Medical University, Salzburg, Austria. [Tur C] Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre, UCL Institute of Neurology, University College London, London, UK. Servei de Neurologia/Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya (CEMCAT), Barcelona, Spain. [Marschallinger H] Marschallinger GeoInformatik, Seekirchen, Austria. [Sellner J] Department of Neurology, Christian Doppler Medical Center, Paracelsus Medical University, Salzburg, Austria. Department of Neurology, Landesklinikum Mistelbach-Gänserndorf, Liechtensteinstr, Mistelbach, Austria. Department of Neurology, Klinikum Rechts der Isar, Technische Universität München, München, Germany
dc.identifier.pmid33445771
dc.identifier.wos000609866000001
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess


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