Unsupervised physics-informed deep learning (N=1) for solving inverse qMRI problems–Relaxometry and field mapping from multi-echo data.


Conference paper


Benslimane I, Jochmann T, Zivadinov R, Schweser F
Proc Intl Soc Mag Reson Med, 2021, p. 330

Cite

Cite

APA
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
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
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.





Follow this website


You need to create an Owlstown account to follow this website.


Sign up

Already an Owlstown member?

Log in