Web of Science: 5 cites, Scopus: 4 cites, Google Scholar: cites,
From raw data to data-analysis for magnetic resonance spectroscopy - the missing link : jMRUI2XML
Mocioiu, Victor (Universitat Autònoma de Barcelona. Departament de Bioquímica i de Biologia Molecular)
Ortega-Martorell, Sandra (Liverpool John Moores University. Department of Mathematics and Statistics)
Olier, Iván (University of Manchester. Institute of Population Health)
Jablonski, Michal (Institute of Scientific Instruments of the CAS (Brno, República Txeca))
Starcukova, Jana (Institute of Scientific Instruments of the CAS (Brno, República Txeca))
Lisboa, Paulo J. G. (Liverpool John Moores University. Department of Mathematics and Statistics)
Arús i Caraltó, Carles (Universitat Autònoma de Barcelona. Departament de Bioquímica i Biologia Molecular)
Julià Sapé, Ma. Margarita (Institut de Biotecnologia i de Biomedicina "Vicent Villar Palasí")

Data: 2015
Resum: Background: Magnetic resonance spectroscopy provides metabolic information about living tissues in a non-invasive way. However, there are only few multi-centre clinical studies, mostly performed on a single scanner model or data format, as there is no flexible way of documenting and exchanging processed magnetic resonance spectroscopy data in digital format. This is because the DICOM standard for spectroscopy deals with unprocessed data. This paper proposes a plugin tool developed for jMRUI, namely jMRUI2XML, to tackle the latter limitation. jMRUI is a software tool for magnetic resonance spectroscopy data processing that is widely used in the magnetic resonance spectroscopy community and has evolved into a plugin platform allowing for implementation of novel features. Results: jMRUI2XML is a Java solution that facilitates common preprocessing of magnetic resonance spectroscopy data across multiple scanners. Its main characteristics are: 1) it automates magnetic resonance spectroscopy preprocessing, and 2) it can be a platform for outputting exchangeable magnetic resonance spectroscopy data. The plugin works with any kind of data that can be opened by jMRUI and outputs in extensible markup language format. Data processing templates can be generated and saved for later use. The output format opens the way for easy data sharing- due to the documentation of the preprocessing parameters and the intrinsic anonymization - for example for performing pattern recognition analysis on multicentre/multimanufacturer magnetic resonance spectroscopy data. Conclusions: jMRUI2XML provides a self-contained and self-descriptive format accounting for the most relevant information needed for exchanging magnetic resonance spectroscopy data in digital form, as well as for automating its processing. This allows for tracking the procedures the data has undergone, which makes the proposed tool especially useful when performing pattern recognition analysis. Moreover, this work constitutes a first proposal for a minimum amount of information that should accompany any magnetic resonance processed spectrum, towards the goal of achieving better transferability of magnetic resonance spectroscopy studies.
Drets: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original. Creative Commons
Llengua: Anglès
Document: article ; recerca ; publishedVersion
Matèria: Magnetic resonance spectroscopy ; Pattern recognition ; Signal processing ; Software development
Publicat a: BMC bioinformatics, Vol. 16, N. 378 (November 2015) , p. 1-11, ISSN 1471-2105

DOI: 10.1186/s12859-015-0796-5
PMID: 26552737

11 p, 2.4 MB

El registre apareix a les col·leccions:
Documents de recerca > Documents dels grups de recerca de la UAB > Centres i grups de recerca (producció científica) > Ciències de la salut i biociències > Institut de Biotecnologia i de Biomedicina (IBB)
Articles > Articles de recerca
Articles > Articles publicats

 Registre creat el 2017-03-08, darrera modificació el 2020-08-15

   Favorit i Compartir