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Proceedings Paper

Generative adversarial network prediction of optical properties from wide-field images (Conference Presentation)
Author(s): Nicholas J. Durr

Paper Abstract

I will present a deep learning framework for content-aware estimation of tissue optical properties from wide-field images. Spatial frequency domain imaging is used to acquire ground-truth measurements of scattering and absorption coefficients of a variety of tissues. A generative network is then adversarially trained to estimate these properties from new tissues directly from unstructured or structured light. This data-driven approach has some advantages in accuracy and speed compared to model-based approaches.

Paper Details

Date Published: 10 March 2020
Proc. SPIE 11222, Molecular-Guided Surgery: Molecules, Devices, and Applications VI, 1122203 (10 March 2020); doi: 10.1117/12.2550569
Show Author Affiliations
Nicholas J. Durr, Johns Hopkins Univ. (United States)

Published in SPIE Proceedings Vol. 11222:
Molecular-Guided Surgery: Molecules, Devices, and Applications VI
Sylvain Gioux; Summer L. Gibbs; Brian W. Pogue, Editor(s)

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