RRTGAN
A software for enhancing the pixel resolution of cone photoreceptor cells from sparsely sampled adaptive optics optical coherence tomography (AOOCT) images.
Details
This software was primarily developed by Vineeta Das and Johnny Tam, with research support from Intramural Research Program of the National Institutes of Health, National Eye Institute. Additional details about the algorithms used can be found in the reference listed below.
The following items are available:
- Readme: for getting started with the installation package
- License: for using the software
- Example images and results: for testing the software.
- Code repository containing the code and example images for testing the software.
We welcome any feedback you may have about the software.
Citation(s)
If any portion of this software is used, please cite the following paper in your publication:
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Vineeta Das, Andrew J. Bower, Nancy Aguilera, Joanne Li, and Johnny Tam, " Artificial intelligence-assisted retinal imaging enables dense pixel sampling from sparse measurements." npj Artificial Intelligence, 1(1), 48.
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