Data-driven SFDI to measure molecular signals from widefield images

Nicholas J. Durr

doi:10.1117/12.2590874

5 March 2021 Data-driven SFDI to measure molecular signals from widefield images

Nicholas J. Durr

Proceedings Volume 11622, Multiscale Imaging and Spectroscopy II; 1162203 (2021) https://doi.org/10.1117/12.2590874
Event: SPIE BiOS, 2021, Online Only

Abstract

Machine learning offers a powerful set of tools to make widefield endoscopic imaging more quantitative. This presentation covers our work in estimating pixel size, topography, optical properties, and molecular chromophores using structured illumination and generative adversarial networks. We aim to create a computational endoscope that will improve computer-aided detection and diagnosis.

Conference Presentation

Citation Download Citation

Nicholas J. Durr "Data-driven SFDI to measure molecular signals from widefield images", Proc. SPIE 11622, Multiscale Imaging and Spectroscopy II, 1162203 (5 March 2021); https://doi.org/10.1117/12.2590874

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