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Robust breast cancer detection in mammography and digital breast tomosynthesis using an annotation-efficient deep learning approach

Crossref DOI link: https://doi.org/10.1038/s41591-020-01174-9

Published Online: 2021-01-11

Published Print: 2021-02

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Lotter, William

Diab, Abdul Rahman

Haslam, Bryan

Kim, Jiye G. https://orcid.org/0000-0002-5232-7748
Grisot, Giorgia

Wu, Eric

Wu, Kevin

Onieva, Jorge Onieva

Boyer, Yun

Boxerman, Jerrold L. https://orcid.org/0000-0002-0594-1542
Wang, Meiyun https://orcid.org/0000-0003-4454-5005
Bandler, Mack

Vijayaraghavan, Gopal R.

Gregory Sorensen, A. https://orcid.org/0000-0001-7750-8206
Funding

Funding for this research was provided by:

U.S. Department of Health & Human Services | NIH | National Cancer Institute (1R44CA240022, 1R37CA240403-01A1)

U.S. Department of Health & Human Services | NIH | National Cancer Institute (1R44CA240022, 1R37CA240403-01A1)

U.S. Department of Health & Human Services | NIH | National Cancer Institute (1R44CA240022, 1R37CA240403-01A1)

U.S. Department of Health & Human Services | NIH | National Cancer Institute (1R44CA240022, 1R37CA240403-01A1)

U.S. Department of Health & Human Services | NIH | National Cancer Institute (1R44CA240022, 1R37CA240403-01A1)

U.S. Department of Health & Human Services | NIH | National Cancer Institute (1R44CA240022, 1R37CA240403-01A1)

U.S. Department of Health & Human Services | NIH | National Cancer Institute (1R44CA240022, 1R37CA240403-01A1)

U.S. Department of Health & Human Services | NIH | National Cancer Institute (1R44CA240022, 1R37CA240403-01A1)

U.S. Department of Health & Human Services | NIH | National Cancer Institute (1R44CA240022, 1R37CA240403-01A1)

National Science Foundation (1938387)

National Science Foundation (1938387)

National Science Foundation (1938387)

National Science Foundation (1938387)

National Science Foundation (1938387)

National Science Foundation (1938387)

National Science Foundation (1938387)

National Science Foundation (1938387)

National Science Foundation (1938387)

National Science Foundation (1938387)

U.S. Department of Health & Human Services | NIH | National Cancer Institute

U.S. Department of Health & Human Services | NIH | National Cancer Institute

U.S. Department of Health & Human Services | NIH | National Cancer Institute

U.S. Department of Health & Human Services | NIH | National Cancer Institute

U.S. Department of Health & Human Services | NIH | National Cancer Institute

U.S. Department of Health & Human Services | NIH | National Cancer Institute

U.S. Department of Health & Human Services | NIH | National Cancer Institute

U.S. Department of Health & Human Services | NIH | National Cancer Institute
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Text and Data Mining valid from 2021-01-11

Version of Record valid from 2021-01-11
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Article History

Received: 1 January 2020

Accepted: 10 November 2020

First Online: 11 January 2021

Competing interests

: W.L., A.R.D., B.H., J.G.K., G.G., J.O.O., Y.B. and A.G.S. are employees of RadNet, the parent company of DeepHealth. M.B. serves as a consultant for DeepHealth. Two patent disclosures have been filed related to the study methods under inventor W.L.

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