Label-free colorectal cancer screening using deep learning and spatial light interference microscopy (SLIM)-Reference-Cited by-同舟云学术

Label-free colorectal cancer screening using deep learning and spatial light interference microscopy (SLIM)

Published:2020-04-01 Issue:4 Volume:5 Page:040805
ISSN:2378-0967
Container-title:APL Photonics
language:en
Short-container-title:APL Photonics

Author:

Zhang Jingfang K.¹²,He Yuchen R.¹²³,Sobh Nahil¹²,Popescu Gabriel¹²³⁴

Affiliation:

1. Quantitative Light Imaging Laboratory, University of Illinois at Urbana-Champaign, 405 N. Matthews Avenue, Urbana, Illinois 61801, USA

2. Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, 405 N. Matthews Avenue, Urbana, Illinois 61801, USA

3. Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, 405 N. Matthews Avenue, Urbana, Illinois 61801, USA

4. Department of Bioengineering, University of Illinois at Urbana-Champaign, 405 N. Matthews Avenue, Urbana, Illinois 61801, USA

Funder

National Science Foundation

National Institutes of Health

Publisher

AIP Publishing

Subject

Computer Networks and Communications,Atomic and Molecular Physics, and Optics

Link

http://aip.scitation.org/doi/pdf/10.1063/5.0004723

Reference29 articles.

1. Quantitative phase imaging in biomedicine

2. Early Prediction of Cancer Progression by Depth-Resolved Nanoscale Mapping of Nuclear Architecture from Unstained Tissue Specimens

3. Quantitative phase imaging for medical diagnosis

4. Spatial light interference microscopy (SLIM)

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