Enhancing resolution in coherent microscopy using deep learning (Conference Presentation)

Kevin de Haan; Tairan Liu; Yair Rivenson; Zhensong Wei; Xin Zeng; Yibo Zhang; Aydogan Ozcan

doi:10.1117/12.2545429

11 March 2020 Enhancing resolution in coherent microscopy using deep learning (Conference Presentation)

Kevin de Haan, Tairan Liu, Yair Rivenson, Zhensong Wei, Xin Zeng, Yibo Zhang, Aydogan Ozcan

Proceedings Volume 11249, Quantitative Phase Imaging VI; 1124904 (2020) https://doi.org/10.1117/12.2545429
Event: SPIE BiOS, 2020, San Francisco, California, United States

Abstract

We report a generative adversarial network (GAN)-based framework to super-resolve both pixel-limited and diffraction-limited images, acquired by coherent microscopy. We experimentally demonstrate a resolution enhancement factor of 2-6× for a pixel-limited imaging system and 2.5× for a diffraction-limited imaging system using lung tissue sections and Papanicolaou (Pap) smear slides. The efficacy of the technique is proven both quantitatively and qualitatively by a direct visual comparison between the network’s output images and the corresponding high-resolution images. Using this data driven technique, the resolution of coherent microscopy can be improved to substantially increase the imaging throughput.

Conference Presentation

Citation Download Citation

Kevin de Haan, Tairan Liu, Yair Rivenson, Zhensong Wei, Xin Zeng, Yibo Zhang, and Aydogan Ozcan "Enhancing resolution in coherent microscopy using deep learning (Conference Presentation)", Proc. SPIE 11249, Quantitative Phase Imaging VI, 1124904 (11 March 2020); https://doi.org/10.1117/12.2545429

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available