Beyond qMRI: Biological tissue properties forom single-subject unsupervised deep learning with theoretical signal constraints


Conference paper


Benslimane I, Grabner G, Hametner S, Jochmann T, Zivadinov R, Schweser F
Proc Intl Soc Mag Reson Med, 2022, p. 370

Cite

Cite

APA   Click to copy
I, B., G, G., S, H., T, J., R, Z., & F, S. (2022). Beyond qMRI: Biological tissue properties forom single-subject unsupervised deep learning with theoretical signal constraints (p. 370).


Chicago/Turabian   Click to copy
I, Benslimane, Grabner G, Hametner S, Jochmann T, Zivadinov R, and Schweser F. “Beyond QMRI: Biological Tissue Properties Forom Single-Subject Unsupervised Deep Learning with Theoretical Signal Constraints.” In , 370. Proc Intl Soc Mag Reson Med, 2022.


MLA   Click to copy
I, Benslimane, et al. Beyond QMRI: Biological Tissue Properties Forom Single-Subject Unsupervised Deep Learning with Theoretical Signal Constraints. 2022, p. 370.


BibTeX   Click to copy

@inproceedings{benslimane2022a,
  title = {Beyond qMRI: Biological tissue properties forom single-subject unsupervised deep learning with theoretical signal constraints},
  year = {2022},
  pages = {370},
  series = {Proc Intl Soc Mag Reson Med},
  author = {I, Benslimane and G, Grabner and S, Hametner and T, Jochmann and R, Zivadinov and F, Schweser}
}





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