Unsupervised content-preserving transformation for optical microscopy
Abstract The development of deep learning and open access to a substantial collection of imaging data together provide a potential solution for computational image transformation, which is gradually changing the landscape of optical imaging and biomedical research. However, current implementations o...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2021-03-01
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| Series: | Light: Science & Applications |
| Online Access: | https://doi.org/10.1038/s41377-021-00484-y |