A deep adversarial model for segmentation-assisted COVID-19 diagnosis using CT images.

Yao HY, Wan WG, Li X

DOI: 10.1186/s13634-022-00842-x
Published: 2022
Container: EURASIP journal on advances in signal processing
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1186/s13634-022-00842-x,
  title = {A deep adversarial model for segmentation-assisted COVID-19 diagnosis using CT images.},
  author = {Yao HY and Wan WG and Li X},
  year = {2022},
  journal = {EURASIP journal on advances in signal processing},
  doi = {10.1186/s13634-022-00842-x},
  url = {https://doi.org/10.1186/s13634-022-00842-x}
}

RIS

TY  - JOUR
TI  - A deep adversarial model for segmentation-assisted COVID-19 diagnosis using CT images.
AU  - Yao HY
AU  - Wan WG
AU  - Li X
PY  - 2022
JO  - EURASIP journal on advances in signal processing
DO  - 10.1186/s13634-022-00842-x
UR  - https://doi.org/10.1186/s13634-022-00842-x
ER  -

APA

HY, Y., WG, W., & X, L. (2022). A deep adversarial model for segmentation-assisted COVID-19 diagnosis using CT images.. EURASIP journal on advances in signal processing. https://doi.org/10.1186/s13634-022-00842-x

Source records

pubmed · retrieved 2026-09-26T04:47:12.949Z