Quantitative phase microscopy using deep neural networks
Deep learning has been proven to achieve ground-breaking accuracy in various tasks. In this paper, we implemented a deep neural network (DNN) to achieve phase retrieval in a wide-field microscope. Our DNN utilized the residual neural network (ResNet) architecture and was trained using the data gener...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
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SPIE
2018
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| Online Access: | http://hdl.handle.net/1721.1/119144 https://orcid.org/0000-0002-7836-0431 https://orcid.org/0000-0002-4140-1404 |