Conference paper
Proc Intl Soc Mag Reson Med, 2021, p. 330
APA
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I, B., T, J., R, Z., & F, S. (2021). Unsupervised physics-informed deep learning (N=1) for solving inverse qMRI problems–Relaxometry and field mapping from multi-echo data. (p. 330).
Chicago/Turabian
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I, Benslimane, Jochmann T, Zivadinov R, and Schweser F. “Unsupervised Physics-Informed Deep Learning (N=1) for Solving Inverse QMRI Problems–Relaxometry and Field Mapping from Multi-Echo Data.” In , 330. Proc Intl Soc Mag Reson Med, 2021.
MLA
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I, Benslimane, et al. Unsupervised Physics-Informed Deep Learning (N=1) for Solving Inverse QMRI Problems–Relaxometry and Field Mapping from Multi-Echo Data. 2021, p. 330.
BibTeX Click to copy
@inproceedings{benslimane2021a,
title = {Unsupervised physics-informed deep learning (N=1) for solving inverse qMRI problems–Relaxometry and field mapping from multi-echo data.},
year = {2021},
pages = {330},
series = {Proc Intl Soc Mag Reson Med},
author = {I, Benslimane and T, Jochmann and R, Zivadinov and F, Schweser}
}