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* Update README.md

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jannisborn authored May 5, 2024
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[![Build Status](https://github.com/jannisborn/covid19_ultrasound/actions/workflows/build.yml/badge.svg)](https://github.com/jannisborn/covid19_ultrasound/actions/workflows/build.yml)

## Summary
This repo contains the code for the paper [`Accelerating Detection of Lung Pathologies with Explainable Ultrasound Image Analysis`](https://www.mdpi.com/2076-3417/11/2/672).

### News
This repo contains the code for the paper `Accelerating Detection of Lung Pathologies with Explainable Ultrasound Image Analysis` which is now [available](https://www.mdpi.com/2076-3417/11/2/672). Please [cite](#Citation) that one instead of our preprint.
- **April '24: We released [COVID-BLUES](https://github.com/NinaWie/COVID-BLUES), a new dataset of 371 videos from 63 patients collected in a prospective clinical study**. Please check out the data and consider using it _instead_ of this one since it is of much higher quality. The paper for this data will appear soon.

### Dataset
Feel free to use (and cite) our dataset. We currently have >200 LUS videos labelled with a diagnostic outcome. Moreover, lung severity scores for 136 videos are made available in the [dataset_metadata.csv](./data/dataset_metadata.csv) under the column **"Lung Severity Score"** from [Gare et al., 2022](https://arxiv.org/abs/2201.07357). Further clinical information (symptoms, visible LUS patterns etc) are provided for some videos. For details see [data/README.md](data/README.md).
Feel free to use (and [cite](#Citation)) our dataset. We currently have >200 LUS videos labelled with a diagnostic outcome. Moreover, lung severity scores for 136 videos are made available in the [dataset_metadata.csv](./data/dataset_metadata.csv) under the column **"Lung Severity Score"** from [Gare et al., 2022](https://arxiv.org/abs/2201.07357). Further clinical information (symptoms, visible LUS patterns etc) are provided for some videos. For details see [data/README.md](data/README.md).

If you are looking for more data, please consider using the 40,000 [carefully simulated LUS images](https://gitlab.com/pulselab/covid19) and paired labels from the paper by [Zhao et al. (2024, *Communications Medicine*)](https://www.nature.com/articles/s43856-024-00463-5). In addition, segmentation labels for a subset of the in vivo data in this repo are also available. For details see [PULSE Lab Repository/README.md](PULSE%20Lab%20Repository/README.md).

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pages={672}
}
```

If you use the severity scores, please cite the [Gare et al., 2022](https://arxiv.org/abs/2201.07357) paper using the following bibtex entry:
```bib
@article{Gare2022WeaklyUltrasound,
author = {Gare, Gautam Rajendrakumar and Tran, Hai V. and deBoisblanc, Bennett P and Rodriguez, Ricardo Luis and Galeotti, John Michael},
title = {{Weakly Supervised Contrastive Learning for Better Severity Scoring of Lung Ultrasound}},
year = {2022},
month = {1},
publisher = {arXiv},
url = {https://arxiv.org/abs/2201.07357},
doi = {10.48550/ARXIV.2201.07357},
arxivId = {2201.07357}
}
```

If you use the 40,000 synthetic images from [Zhao et al., 2024](https://www.nature.com/articles/s43856-024-00463-5), please cite their paper with the following bibtex entry:
```bib
@article{zhao2024detection,
title={Detection of COVID-19 features in lung ultrasound images using deep neural networks},
author={Zhao, Lingyi and Fong, Tiffany Clair and Bell, Muyinatu A Lediju},
journal={Communications Medicine},
volume={4},
number={1},
pages={41},
year={2024},
publisher={Nature Publishing Group UK London}
}
```

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