Complexity of ballooned hepatocyte feature recognition: Defining a training atlas for artificial intelligence-based imaging in NAFLD

Authors

Elizabeth M. Brunt, Washington University School of Medicine in St. Louis
et al.

Journal

Journal of Hepatology

Publication Date

5-1-2022

Volume

76

Issue

5

First Page

1030

Last Page

1041

Document Type

Open Access Publication

DOI

10.1016/j.jhep.2022.01.011

Rights and Permissions

Brunt EM, Clouston AD, Goodman Z, Guy C, Kleiner DE, Lackner C, Tiniakos DG, Wee A, Yeh M, Leow WQ, Chng E, Ren Y, Boon Bee GG, Powell EE, Rinella M, Sanyal AJ, Neuschwander-Tetri B, Younossi Z, Charlton M, Ratziu V, Harrison SA, Tai D, Anstee QM. Complexity of ballooned hepatocyte feature recognition: Defining a training atlas for artificial intelligence-based imaging in NAFLD. J Hepatol. 2022 May;76(5):1030-1041. doi: 10.1016/j.jhep.2022.01.011. This is an open access article distributed under the terms of the Creative Commons CC-BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Recommended Citation

Brunt, Elizabeth M. and et al., "Complexity of ballooned hepatocyte feature recognition: Defining a training atlas for artificial intelligence-based imaging in NAFLD." Journal of Hepatology. 76, 5. 1030 - 1041. (2022).
https://digitalcommons.wustl.edu/oa_4/1520

Additional Links

Supplemental material is available for this article at publisher site.