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  This repository contains the AeroPath dataset described in ["_AeroPath: An airway segmentation benchmark dataset with challenging pathology_"](https://arxiv.org/abs/2311.01138). A web application was also developed in the study, to enable users to easily test our deep learning model on their own data. The application was developed using [Gradio](https://www.gradio.app) for the frontend and the segmentation is performed using the [Raidionics](https://raidionics.github.io/) backend.
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- The dataset can be accessed [here]([https://github.com/raidionics/AeroPath/releases](https://zenodo.org/records/10069289)).
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  ## [Dataset structure](https://github.com/raidionics/AeroPath#data-structure)
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  This repository contains the AeroPath dataset described in ["_AeroPath: An airway segmentation benchmark dataset with challenging pathology_"](https://arxiv.org/abs/2311.01138). A web application was also developed in the study, to enable users to easily test our deep learning model on their own data. The application was developed using [Gradio](https://www.gradio.app) for the frontend and the segmentation is performed using the [Raidionics](https://raidionics.github.io/) backend.
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+ The dataset can be accessed [here](https://zenodo.org/records/10069289).
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  ## [Dataset structure](https://github.com/raidionics/AeroPath#data-structure)
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