Denoising in 3D (Planaria nuclei)
This work (method and data) is part of Content-aware image restoration: pushing the limits of fluorescence microscopy by Martin Weigert et al. in Nature Methods.
Input and reconstructions of a trained CARE Network on previously unseen live imaging data of Schmidtea mediterranea.
We consistently observed that the reconstructed image data was of very high quality, even if the signal to noise ratio (SNR) of the input was very low, e.g. being acquired with a 60-fold reduced light-dosage.
The trained model is published for demonstration purposes. You can try it via Fiji and KNIME.
To run the demo in Fiji, follow these instructions.
To run the demo in KNIME, follow these instructions.
Enabling live-cell imaging of the flatworm S. mediterranea.
Denoising results on an entire multi-tiled S. mediterranea samples.