Harmonizing 10,000 connectomes: site-invariant representation learning for multi-site analysis of network connectivity and cognitive impairment

Nancy R. Newlin, Michael E. Kim, Praitayini Kanakaraj, Elyssa McMaster, Chloe Cho, Chenyu Gao, Timothy J. Hohman, Lori Beason-Held, Susan M. Resnick, Sid E. O’Bryant, Nicole Phillips, Robert C. Barber, David A. Bennett, Lisa L. Barnes, Sarah Biber, Sterling Johnson, Derek Archer, Zhiyuan Li, Lianrui Zuo, Daniel Moyer, Bennett A. Landman

Open source

DOI: 10.1117/1.jmi.12.6.064001
Published: 2025-11-06
Container: Journal of Medical Imaging
Publisher: SPIE-Intl Soc Optical Eng
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1117/1.jmi.12.6.064001,
  title = {Harmonizing 10,000 connectomes: site-invariant representation learning for multi-site analysis of network connectivity and cognitive impairment},
  author = {Nancy R. Newlin and Michael E. Kim and Praitayini Kanakaraj and Elyssa McMaster and Chloe Cho and Chenyu Gao and Timothy  J. Hohman and Lori Beason-Held and Susan M. Resnick and Sid E. O’Bryant and Nicole Phillips and Robert C. Barber and David A. Bennett and Lisa L. Barnes and Sarah Biber and Sterling Johnson and Derek Archer and Zhiyuan Li and Lianrui Zuo and Daniel Moyer and Bennett A. Landman},
  year = {2025},
  journal = {Journal of Medical Imaging},
  doi = {10.1117/1.jmi.12.6.064001},
  url = {https://doi.org/10.1117/1.jmi.12.6.064001}
}

RIS

TY  - JOUR
TI  - Harmonizing 10,000 connectomes: site-invariant representation learning for multi-site analysis of network connectivity and cognitive impairment
AU  - Nancy R. Newlin
AU  - Michael E. Kim
AU  - Praitayini Kanakaraj
AU  - Elyssa McMaster
AU  - Chloe Cho
AU  - Chenyu Gao
AU  - Timothy  J. Hohman
AU  - Lori Beason-Held
AU  - Susan M. Resnick
AU  - Sid E. O’Bryant
AU  - Nicole Phillips
AU  - Robert C. Barber
AU  - David A. Bennett
AU  - Lisa L. Barnes
AU  - Sarah Biber
AU  - Sterling Johnson
AU  - Derek Archer
AU  - Zhiyuan Li
AU  - Lianrui Zuo
AU  - Daniel Moyer
AU  - Bennett A. Landman
PY  - 2025
JO  - Journal of Medical Imaging
DO  - 10.1117/1.jmi.12.6.064001
UR  - https://doi.org/10.1117/1.jmi.12.6.064001
ER  -

APA

Newlin, N. R., Kim, M. E., Kanakaraj, P., McMaster, E., Cho, C., Gao, C., Hohman, T. J., Beason-Held, L., Resnick, S. M., O’Bryant, S. E., Phillips, N., Barber, R. C., Bennett, D. A., Barnes, L. L., Biber, S., Johnson, S., Archer, D., Li, Z., Zuo, L., Moyer, D., & Landman, B. A. (2025). Harmonizing 10,000 connectomes: site-invariant representation learning for multi-site analysis of network connectivity and cognitive impairment. Journal of Medical Imaging. https://doi.org/10.1117/1.jmi.12.6.064001

Source records

crossref · retrieved 2026-09-26T17:13:28.211Z