J 2015

From raw data to data-analysis for magnetic resonance spectroscopy - the missing link: jMRUI2XML

MOCIOIU, V, S ORTEGA-MARTORELL, I OLIER, Michal JABLONSKI, Jana STARČUKOVÁ et. al.

Základní údaje

Originální název

From raw data to data-analysis for magnetic resonance spectroscopy - the missing link: jMRUI2XML

Autoři

MOCIOIU, V, S ORTEGA-MARTORELL, I OLIER, Michal JABLONSKI, Jana STARČUKOVÁ, P LISBOA, C ARUS a M JULIA-SAPE

Vydání

BMC Bioinformatics, London, BioMed Central, 2015, 1471-2105

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Utajení

není předmětem státního či obchodního tajemství

Odkazy

Impakt faktor

Impact factor: 2.435

DOI

UT WoS

000364364400001

Klíčová slova anglicky

Magnetic resonance spectroscopy; Pattern recognition; Signal processing; Software development
Změněno: 20. 10. 2017 17:10, Ing. Michal Jablonski, Ph.D.

Anotace

V originále

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.