Avoiding data loss: Synthetic MRIs generated from diffusion imaging can replace corrupted structural acquisitions for freesurfer-seeded tractography

Jeremy Beaumont, Giulio Gambarota, Marita Prior, Jurgen Fripp, Lee B. Reid

Open source

DOI: 10.1371/journal.pone.0247343
Published: 2022-02-18
Container: PLOS ONE
Publisher: Public Library of Science (PLoS)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1371/journal.pone.0247343,
  title = {Avoiding data loss: Synthetic MRIs generated from diffusion imaging can replace corrupted structural acquisitions for freesurfer-seeded tractography},
  author = {Jeremy Beaumont and Giulio Gambarota and Marita Prior and Jurgen Fripp and Lee B. Reid},
  year = {2022},
  journal = {PLOS ONE},
  doi = {10.1371/journal.pone.0247343},
  url = {https://doi.org/10.1371/journal.pone.0247343}
}

RIS

TY  - JOUR
TI  - Avoiding data loss: Synthetic MRIs generated from diffusion imaging can replace corrupted structural acquisitions for freesurfer-seeded tractography
AU  - Jeremy Beaumont
AU  - Giulio Gambarota
AU  - Marita Prior
AU  - Jurgen Fripp
AU  - Lee B. Reid
PY  - 2022
JO  - PLOS ONE
DO  - 10.1371/journal.pone.0247343
UR  - https://doi.org/10.1371/journal.pone.0247343
ER  -

APA

Beaumont, J., Gambarota, G., Prior, M., Fripp, J., & Reid, L. B. (2022). Avoiding data loss: Synthetic MRIs generated from diffusion imaging can replace corrupted structural acquisitions for freesurfer-seeded tractography. PLOS ONE. https://doi.org/10.1371/journal.pone.0247343

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crossref · retrieved 2026-09-26T07:38:49.704Z