UniFMIR: Pre-training a Foundation Model for Universal Fluorescence Microscopy Image Restoration

This repository contains the preprocessed dataset for [UniFMIR](https://github.com/cxm12/UNiFMIR/). All training and test data involved in the experiments are publicly available datasets. Licenses of the original dataset are applied. You can refer to the Github repository for details. * The 3D denoising/isotropic reconstruction/projection datasets can be downloaded from [Content Aware Image Restoration dataset](https://publications.mpi-cbg.de/publications-sites/7207/). `Projection_Flywing/train_data/my_training_data.npz` are generated according to the [CSBDeep](http://csbdeep.bioimagecomputing.com/doc/). * The SR dataset can be downloaded from [BioSR dataset](https://doi.org/10.6084/m9.figshare.13264793). The dataset is augmented according to the instructions in [DFCAN](https://github.com/qc17-THU/DL-SR/tree/main#train-a-new-model) and `my_training_data.npz` files are generated following [CSBDeep](http://csbdeep.bioimagecomputing.com/doc/datagen.html). * The Volumetric reconstruction dataset are from [VCD-LFM dataset](https://doi.org/10.5281/zenodo.4390067). The dataset is prepared according to the instructions in [VCD-Net](https://github.com/feilab-hust/VCD-Net). * DeepBacs dataset can be downloaded from [DeepBacs dataset](https://zenodo.org/record/6460867). We split the dataset into 5 folds for cross-validation. Shareloc dataset can be downloaded from [Shareloc dataset](https://zenodo.org/record/7234161). The data paths should be as follows: ``` VCD/vcdnet/ CSB/DataSet/ Denoising_Planaria/ Denoising_Tribolium/ Isotropic/Isotropic_Liver/ Projection_Flywing/ BioSR_WF_to_SIM/DL-SR-main/dataset/ Synthetic_tubulin_gfp/ Synthetic_tubulin_granules/ DeepBacs/ Shareloc/ ```