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Updated Data section in README regarding access + CoLab badge
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README.md
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[](https://github.com/DAVFoundation/captain-n3m0/blob/master/LICENSE)
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[](https://github.com/raidionics/AeroPath/actions/workflows/deploy.yml)
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<a target="_blank" href="https://huggingface.co/spaces/andreped/AeroPath"><img src="https://img.shields.io/badge/🤗%20Hugging%20Face-Spaces-yellow.svg"></a>
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[](https://doi.org/10.5281/zenodo.10069288)
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[](https://arxiv.org/abs/2311.01138)
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The dataset is made openly available at [Zenodo](https://zenodo.org/records/10069289) and [the Hugging Face Hub](https://huggingface.co/datasets/andreped/AeroPath). Click any of the two hyperlinks to access the dataset.
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## [Dataset
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```
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└── AeroPath.zip
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[](https://github.com/DAVFoundation/captain-n3m0/blob/master/LICENSE)
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[](https://github.com/raidionics/AeroPath/actions/workflows/deploy.yml)
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<a target="_blank" href="https://huggingface.co/spaces/andreped/AeroPath"><img src="https://img.shields.io/badge/🤗%20Hugging%20Face-Spaces-yellow.svg"></a>
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<a href="https://colab.research.google.com/gist/andreped/6070d1d2914a9ce5847d4b3e687188b7/aeropath-load-dataset-example.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
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[](https://doi.org/10.5281/zenodo.10069288)
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[](https://arxiv.org/abs/2311.01138)
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The dataset is made openly available at [Zenodo](https://zenodo.org/records/10069289) and [the Hugging Face Hub](https://huggingface.co/datasets/andreped/AeroPath). Click any of the two hyperlinks to access the dataset.
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## [Dataset](https://github.com/raidionics/AeroPath#data)
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### [Accessing dataset](https://github.com/raidionics/AeroPath#accessing-dataset)
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The dataset contains 27 CTs with corresponding airways and lung annotations. The folder structure is described below.
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The easiest way to access the data is through Python with Hugging Face's [datasets](https://pypi.org/project/datasets/) package:
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```
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from datasets import load_dataset
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# downloads data from Zenodo through the Hugging Face hub
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# - might take several minutes (~5 minutes in CoLab)
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dataset = load_dataset("andreped/AeroPath")
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print(dataset)
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# list paths of all available patients and corresponding features (ct/airways/lungs)
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for d in dataset["test"]:
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print(d)
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```
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A detailed interactive demo on how to load and work with the data can be seen on CoLab: <a href="https://colab.research.google.com/gist/andreped/6070d1d2914a9ce5847d4b3e687188b7/aeropath-load-dataset-example.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
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### [Dataset structure](https://github.com/raidionics/AeroPath#data-structure)
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```
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└── AeroPath.zip
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