Deep learning-enabled holography (Conference Presentation)

Aydogan Ozcan

doi:10.1117/12.2536260

10 March 2020 Deep learning-enabled holography (Conference Presentation)

Aydogan Ozcan

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Proceedings Volume 11251, Label-free Biomedical Imaging and Sensing (LBIS) 2020; 112511M (2020) https://doi.org/10.1117/12.2536260
Event: SPIE BiOS, 2020, San Francisco, California, United States

Abstract

Deep learning is a class of machine learning techniques that uses multi-layered artificial neural networks for automated analysis of signals or data. The name comes from the general structure of deep neural networks, which consist of several layers of artificial neurons, each performing a nonlinear operation, stacked over each other. Beyond its main stream applications such as the recognition and labeling of specific features in images, deep learning holds numerous opportunities for revolutionizing image formation, reconstruction and sensing fields. In this presentation, I will provide an overview of some of our recent work on the use of deep neural networks in advancing holographic microscopy and sensing systems, also covering their biomedical applications.

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Aydogan Ozcan "Deep learning-enabled holography (Conference Presentation)", Proc. SPIE 11251, Label-free Biomedical Imaging and Sensing (LBIS) 2020, 112511M (10 March 2020); https://doi.org/10.1117/12.2536260

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KEYWORDS

Holography

Neural networks

3D image reconstruction

Artificial neural networks

Image acquisition

Machine learning

Microscopy

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