DL4MicEverywhere / denoiseg-zerocostdl4mic / 1.14.1

denoiseg-zerocostdl4mic implementation.

Joint denoising and binary segmentation of 2D images. DenoiSeg 2D is deep-learning method that can be used to jointly denoise and segment 2D microscopy images. The benefits of using DenoiSeg (compared to other Deep Learning-based segmentation methods) are more prononced when only a few annotated images are available. However, the denoising part requires many images to perform well. All the noisy images don't need to be labeled to train DenoiSeg. Note - visit the ZeroCostDL4Mic wiki to check the original publications this network is based on and make sure you cite these.
Tags
AMD64colabnotebookdenoisingZeroCostDL4Mic
Citation
https://doi.org/10.1038/s41467-021-22518-0von Chamier, L., Laine, R.F., Jukkala, J. et al. Democratising deep learning for microscopy with ZeroCostDL4Mic. Nat Commun 12, 2276 (2021). https://doi.org/10.1038/s41467-021-22518-0
https://doi.org/10.1007/978-3-030-66415-2_21Buchholz TO., Prakash M., Schmidt D., Krull A., Jug F. (2020) DenoiSeg: Joint Denoising and Segmentation. In: Bartoli A., Fusiello A. (eds) Computer Vision – ECCV 2020 Workshops. ECCV 2020. Lecture Notes in Computer Science, vol 12535. Springer, Cham. https://doi.org/10.1007/978-3-030-66415-2_21
Solution written by
DL4MicEverywhere team
album team

Arguments

--path
What is your working path? (default value: .)

Usage instructions

Please follow this link for details on how to install and run this solution.