76 citations · 84 across the 5 of their papers we have counts for
5 papers
Synthetic Data in MR Spectroscopy: Current Practices, Applications, and Considerations
John T. LaMaster, Aaron T. Gudmundson, Alireza Abaei +75
The use of synthetic data has emerged as an essential tool in Magnetic Resonance Spectroscopy (MRS) research and applications, providing advantages for optimization of acquisition,…
WALINET: A water and lipid identification convolutional Neural Network for nuisance signal removal in 1H MR Spectroscopic Imaging
Paul Weiser, Georg Langs, Stanislav Motyka +5
Purpose. Proton Magnetic Resonance Spectroscopic Imaging (1H-MRSI) provides non-invasive spectral-spatial mapping of metabolism. However, long-standing problems in whole-brain 1H-M…
Deep-ER: Deep Learning ECCENTRIC Reconstruction for fast high-resolution neurometabolic imaging
Paul Weiser, Georg Langs, Wolfgang Bogner +11
Introduction: Altered neurometabolism is an important pathological mechanism in many neurological diseases and brain cancer, which can be mapped non-invasively by Magnetic Resonanc…
Predicting dynamic, motion-related changes in B0 field in the brain at a 7 T MRI using a subject-specific fine-tuned U-net
Stanislav Motyka, Paul Weiser, Beata Bachrata +11
Subject movement during the magnetic resonance examination is inevitable and causes not only image artefacts but also deteriorates the homogeneity of the main magnetic field (B0),…
Super-Resolution 1H Magnetic Resonance Spectroscopic Imaging utilizing Deep Learning
Zohaib Iqbal, Dan Nguyen, Gilbert Hangel +3
Magnetic resonance spectroscopic imaging (SI) is a unique imaging technique that provides biochemical information from in vivo tissues. The 1H spectra acquired from several spatial…