Data for: "Label2label: Training a neural network to selectively restore cellular structures in fluorescence microscopy"

Dataset

Description

This dataset contains the image data that was used to generate the training data for label2label training, as well as the trained models shown in Kölln et al., 2022, J Cell Sci. doi: https://doi.org/10.1242/jcs.258994. Changes that are required to replicate this work with the CSBDeep framework are outlined in 'readme.txt'. See also example Jupyter notebooks.
Date made available11 Feb 2022
PublisherUniversity of Strathclyde
Date of data production2020 - 2021

Contact

Access Dataset

  • data_actin.zip

    File: application/zip, 2.89 GB

    Type: Dataset

    Licence: CC BY 4.0

  • data_caveolae.zip

    File: application/zip, 4.16 GB

    Type: Dataset

    Licence: CC BY 4.0

  • data_paxillin.zip

    File: application/zip, 3.07 GB

    Type: Dataset

    Licence: CC BY 4.0

  • data_tubulin.zip

    File: application/zip, 2.49 GB

    Type: Dataset

    Licence: CC BY 4.0

  • pretrained.zip

    File: application/zip, 1.26 GB

    Type: Dataset

    Licence: CC BY 4.0

  • example.ipynb

    File: application/octet-stream, 13.8 KB

    Type: Dataset

    Licence: CC BY 4.0

  • prediction.ipynb

    File: application/octet-stream, 8.38 KB

    Type: Dataset

    Licence: CC BY 4.0

  • readme.txt

    File: text/plain, 4.53 KB

    Type: Dataset

    Licence: CC BY 4.0

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