Generative adversarial networks in biophotonics: a tutorial with examples (Conference Presentation)

Nicholas J. Durr

doi:10.1117/12.2551387

6 March 2020 Generative adversarial networks in biophotonics: a tutorial with examples (Conference Presentation)

Nicholas J. Durr

Proceedings Volume 11211, Photonics in Dermatology and Plastic Surgery 2020; 112110C (2020) https://doi.org/10.1117/12.2551387
Event: SPIE BiOS, 2020, San Francisco, California, United States

Abstract

Generative adversarial networks (GANs) are among the most interesting and powerful tools in deep learning. GANs are capable of efficiently generating realistic new images given a relatively small set of training examples, enabling many exciting possibilities in biophotonics. This tutorial will introduce the basic concepts and tools useful for creating GAN models. Additionally, several emerging applications of GANs in biophotonics will be covered, including: noise reduction, resolution enhancement, histological analysis, lesion detection, and lesion classification.

Conference Presentation

Citation Download Citation

Nicholas J. Durr "Generative adversarial networks in biophotonics: a tutorial with examples (Conference Presentation)", Proc. SPIE 11211, Photonics in Dermatology and Plastic Surgery 2020, 112110C (6 March 2020); https://doi.org/10.1117/12.2551387

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