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Peer-Reviewed Publication
Light Sci Appl2022;11(1):300.October 14, 2022Journal Article

Deep learning accelerates whole slide imaging for next-generation digital pathology applications.

Yair Rivenson1,2, Aydogan Ozcan3,4,5,6
1Pictor Labs, Inc., Los Angeles, USA. rivenson@pictorlabs.ai.
2Electrical and Computer Engineering Department, University of California, Los Angeles, 90095, CA, USA. rivenson@pictorlabs.ai.
3Electrical and Computer Engineering Department, University of California, Los Angeles, 90095, CA, USA.
4Bioengineering Department, University of California, Los Angeles, 90095, CA, USA.
5California NanoSystems Institute (CNSI), University of California, Los Angeles, 90095, CA, USA.
6Department of Surgery, David Geffen School of Medicine, University of California, Los Angeles, 90095, CA, USA.
PubMed PMC DOI PDF

Abstract

Deep learning demonstrates the ability to significantly increase the scanning speed of whole slide imaging in histology. This transformative solution can be used to further accelerate the adoption of digital pathology.

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