Holo2Bright Dataset (holo2bright_dataset)

Overview

This DeepTrackAI repository provides a copy of the Holo2Bright dataset, consisting of unpaired holographic and bright-field microscopy images of marine microplankton.
The dataset originates from [Bachimanchi et al., eLife, 2022] (https://doi.org/10.7554/eLife.79760), where it was used to train and evaluate deep learning models for reconstructing bright-field images from holograms.

Summary

• Number of images:
  • Training set: 4,500 holographic + 880 bright-field images
  • Test set: 4,500 holographic + 244 bright-field images
• Image size: 256 × 256 pixels
• Format: 8-bit grayscale PNG

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Original Source

• Title: Microplankton life histories revealed by holographic microscopy and deep learning
• Authors: Harshith Bachimanchi, Benjamin Midtvedt, Daniel Midtvedt, Erik Selander, Giovanni Volpe
• Journal: eLife, 11:e79760 (2022)
• DOI: 10.7554/eLife.79760

If you use this dataset in your research, you must follow the licensing requirements and properly attribute the original authors.

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Dataset Structure

/holo2bright_dataset
├── train/
│   ├── holograms/          # 4,500 holographic images (256×256 PNG)
│   └── brightfield/        # 880 bright-field images (256×256 PNG)
└── test/
    ├── holograms/          # 4,500 holographic images (256×256 PNG)
    └── brightfield/        # 244 bright-field images (256×256 PNG)

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How to Access the Data

Clone the Repository

git clone https://github.com/DeepTrackAI/holo2bright_dataset
cd holo2bright_dataset

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Attribution

Cite the paper:

Bachimanchi H, Midtvedt B, Midtvedt D, Selander E, Volpe G. Microplankton life histories revealed by holographic microscopy and deep learning. eLife 11:e79760 (2022). https://doi.org/10.7554/eLife.79760

@article{bachimanchi2022microplankton,
  title={Microplankton life histories revealed by holographic microscopy and deep learning},
  author={Bachimanchi, Harshith and Midtvedt, Benjamin and Midtvedt, Daniel and Selander, Erik and Volpe, Giovanni},
  journal={eLife},
  volume={11},
  pages={e79760},
  year={2022},
  publisher={eLife Sciences Publications Limited},
  doi={10.7554/eLife.79760}
}

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License

This dataset is shared under the Creative Commons Attribution 4.0 International License, following the original licensing terms.