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

Yair Rivenson; Aydogan Ozcan

doi:10.1038/s41377-022-00999-y

Light: Science & Applications (Oct 2022)

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

Yair Rivenson,
Aydogan Ozcan

Affiliations

Yair Rivenson: Pictor Labs, Inc.
Aydogan Ozcan: Electrical and Computer Engineering Department, University of California

DOI: https://doi.org/10.1038/s41377-022-00999-y
Journal volume & issue: Vol. 11, no. 1
pp. 1 – 3

Abstract

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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.

Published in Light: Science & Applications

ISSN: 2047-7538 (Online)
Publisher: Nature Publishing Group
Country of publisher: United Kingdom
LCC subjects: Technology: Engineering (General). Civil engineering (General): Applied optics. Photonics; Science: Physics: Optics. Light
Website: https://www.nature.com/lsa/

About the journal