Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

PhaseStain: Deep Learning-based Histological Staining of Quantitative Phase Images

Not Accessible

Your library or personal account may give you access

Abstract

We demonstrate a digital staining framework that transforms quantitative phase images of label-free tissue sections to match the brightfield microscopy images of the same sections, after histological staining. Inference of multiple tissue-stain combinations is demonstrated.

© 2019 The Author(s)

PDF Article
More Like This
Deep Learning Enables Virtual Histological Staining of Label-free Tissue Sections Using Auto-fluorescence

Yair Rivenson, Hongda Wang, Kevin de Haan, Zhensong Wei, and Aydogan Ozcan
ATu4K.6 CLEO: Applications and Technology (CLEO_AT) 2019

Deep Learning-Based Virtual Staining of Unlabeled Tissue Samples

Kevin de Haan, Yair Rivenson, Zhensong Wei, Hongda Wang, Tairan Liu, W. Dean Wallace, and Aydogan Ozcan
MM3A.3 Microscopy Histopathology and Analytics (Microscopy) 2020

Deep-Learning-Based Virtual H&E Staining Using Total-Absorption Photoacoustic Remote Sensing (TA-PARS)

Marian Boktor, Benjamin Ecclestone, Vlad Pekar, Deepak Dinakaran, John R. Mackey, Paul Fieguth, and Parsin Haji Reza
MS4A.3 Microscopy Histopathology and Analytics (Microscopy) 2022

References

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2022 | Optica Publishing Group. All Rights Reserved