Deep learning-based transformation of H&E stained tissues into special stains

Kevin de Haan; Yijie Zhang; Jonathan E. Zuckerman; Tairan Liu; Anthony E. Sisk; Miguel F. P. Diaz; Kuang-Yu Jen; Alexander Nobori; Sofia Liou; Sarah Zhang; Rana Riahi; Yair Rivenson; W. Dean Wallace; Aydogan Ozcan

doi:10.1038/s41467-021-25221-2

Nature Communications (Aug 2021)

Deep learning-based transformation of H&E stained tissues into special stains

Kevin de Haan,
Yijie Zhang,
Jonathan E. Zuckerman,
Tairan Liu,
Anthony E. Sisk,
Miguel F. P. Diaz,
Kuang-Yu Jen,
Alexander Nobori,
Sofia Liou,
Sarah Zhang,
Rana Riahi,
Yair Rivenson,
W. Dean Wallace,
Aydogan Ozcan

Affiliations

Kevin de Haan: Electrical and Computer Engineering Department, University of California
Yijie Zhang: Electrical and Computer Engineering Department, University of California
Jonathan E. Zuckerman: Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles
Tairan Liu: Electrical and Computer Engineering Department, University of California
Anthony E. Sisk: Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles
Miguel F. P. Diaz: Kaiser Permanente Los Angeles Medical Center, Department of Pathology
Kuang-Yu Jen: Department of Pathology and Laboratory Medicine, University of California at Davis
Alexander Nobori: Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles
Sofia Liou: Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles
Sarah Zhang: Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles
Rana Riahi: Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles
Yair Rivenson: Electrical and Computer Engineering Department, University of California
W. Dean Wallace: Department of Pathology and Laboratory Medicine, Keck School of Medicine of USC
Aydogan Ozcan: Electrical and Computer Engineering Department, University of California

DOI: https://doi.org/10.1038/s41467-021-25221-2
Journal volume & issue: Vol. 12, no. 1
pp. 1 – 13

Abstract

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Performing multiple histological stains on a biopsy can be costly and time consuming. Here the authors present a method for the digital transformation of H&E stained tissue into special stains (e.g., PAS, Masson’s Trichrome and Jones silver stain), and demonstrate that it improves diagnoses over the use of H&E only.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

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