JPP_review_code_2020

This is the repository for the open-source code described in Mannam, Varun, Yide Zhang, Xiaotong Yuan, Cara Ravasio, and Scott Howard. "Machine learning for faster and smarter fluorescence lifetime imaging microscopy." Journal of Physics: Photonics (2020).

@article{mannam2020machine,
  title={Machine learning for faster and smarter fluorescence lifetime imaging microscopy},
  author={Mannam, Varun and Zhang, Yide and Yuan, Xiaotong and Ravasio, Cara and Howard, Scott},
  journal={Journal of Physics: Photonics},
  year={2020},
  publisher={IOP Publishing}
}

Lifetime denoising using pretrained Noise2Noise-NBN model:

#Images: The lifetime images used in the inference stage can be downloaded from here https://curate.nd.edu/show/mw22v40954f

#Citation for dataset: Please cite the FMLD dataset using the following format: Mannam, Varun. “Fluorescence Microscopy Lifetime Denoising (FMLD) Dataset.” Notre Dame, January 1, 2020. https://doi.org/10.7274/r0-18da-9m58.

Code is available here:

https://github.com/ND-HowardGroup/Lifetime_denoising_JPP

Results:

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Estimation of lifetime from intensity

#Images: The training and test dataset can be downloaded from here https://curate.nd.edu/show/jd472v2759b

#Citation for dataset: Please cite the LFI dataset using the following format: Mannam, Varun. “Lifetime From Intensity (LFI) Dataset.” Notre Dame, August 13, 2019. https://doi.org/10.7274/r0-ac46-ft93.

Code is available here:

https://github.com/ND-HowardGroup/Lifetime_from_intensity

Results:

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License & Copyright

© 2020 Varun Mannam, University of Notre Dame

Licensed under the GPL