Noise2Average: An iterative residual learning strategy for image denoising without clean data.

Li Z, Li Z, Bilgic B, Ying K, Salat DH, Polimeni JR, Liao H, Huang SY, Tian Q

DOI: 10.1162/imag.a.1163
Published: 2026
Container: Imaging neuroscience (Cambridge, Mass.)
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1162/imag.a.1163,
  title = {Noise2Average: An iterative residual learning strategy for image denoising without clean data.},
  author = {Li Z and Li Z and Bilgic B and Ying K and Salat DH and Polimeni JR and Liao H and Huang SY and Tian Q},
  year = {2026},
  journal = {Imaging neuroscience (Cambridge, Mass.)},
  doi = {10.1162/imag.a.1163},
  url = {https://doi.org/10.1162/imag.a.1163}
}

RIS

TY  - JOUR
TI  - Noise2Average: An iterative residual learning strategy for image denoising without clean data.
AU  - Li Z
AU  - Li Z
AU  - Bilgic B
AU  - Ying K
AU  - Salat DH
AU  - Polimeni JR
AU  - Liao H
AU  - Huang SY
AU  - Tian Q
PY  - 2026
JO  - Imaging neuroscience (Cambridge, Mass.)
DO  - 10.1162/imag.a.1163
UR  - https://doi.org/10.1162/imag.a.1163
ER  -

APA

Z, L., Z, L., B, B., K, Y., DH, S., JR, P., H, L., SY, H., & Q, T. (2026). Noise2Average: An iterative residual learning strategy for image denoising without clean data.. Imaging neuroscience (Cambridge, Mass.). https://doi.org/10.1162/imag.a.1163

Source records

pubmed · retrieved 2026-09-25T01:15:49.506Z