Synthetic MR spectroscopy data

Kreis, Roland; Rizzo, Rudy

doi:10.48620/229

Synthetic MR spectroscopy data

Project description

Synthetic MR spectroscopy data for quantification purposes of use for model fitting and training neural networks. Brain metabolites with variation in concentration, shim, and background. For details see: doi: 10.1002/mrm.29561

Data Availability

Open

Contact Person

Kreis, Roland

Department for BioMedical Research (DBMR)

Contributors

Kreis, Roland	Department for BioMedical Research (DBMR)
Rizzo, Rudy	Department for BioMedical Research (DBMR)

DOI

10.48620/229

Organization(s)

Department for BioMedical Research (DBMR)

Institute of Diagnostic and Interventional Neuroradiology

Department for BioMedical Research (DBMR)

Languages

en

Subject(s)

Dewey Decimal Classification > 600 Technology > 610 Medicine & health

Keyword(s)

magnetic resonance spectroscopy

•

simulations

•

training data

Rights URI

Attribution (CC BY 4.0)

Boris Publication

Rizzo, Rudy; Dziadosz, Martyna; Kyathanahally, Sreenath P; Shamaei, Amirmohammad; Kreis, Roland (2023). Quantification of MR spectra by deep learning in an idealized setting: Investigation of forms of input, network architectures, optimization by ensembles of networks, and training bias. Magnetic resonance in medicine, 89(5), pp. 1707-1727. Wiley-Liss 10.1002/mrm.29561 <http://dx.doi.org/10.1002/mrm.29561>

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Synthetic MR spectroscopy data

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