--- a +++ b/README.md @@ -0,0 +1,117 @@ +# COVID-19 Chest X-ray Lung Bounding Boxes Dataset + + + +## Intro + +<!-- +<img src="https://user-images.githubusercontent.com/33668152/86773453-7ed8cc80-c077-11ea-975a-b917800389a4.png" alt="X-ray" align="right" width="300" /> +--> + +Lung Bounding Boxes of COVID-19 Chest X-ray Dataset. + +Go [here](#download-the-dataset) if you don't have time. + +--- + +## Table of Contents + +- [Motivation](#motivation) +- [About the Dataset](#about-the-dataset) +- [Download the Dataset](#download-the-dataset) +- [Links and References](#links-and-references) +- [Who are we](#who-are-we) +- [Contact us](#contact-us) +- [License](#license) + +--- + +## Motivation + +In this pandemic situation, our aim is to help researchers to find out a solution. In order to do that we are aiming to provide them with proper datasets that makes the process easier. + +A [repository](https://github.com/ieee8023/covid-chestxray-dataset) to build a public open dataset of chest X-ray and CT images of patients which are positive or suspected of COVID-19 or other viral and bacterial pneumonias (MERS, SARS, and ARDS.) was created by [Joseph Paul Cohen](https://github.com/ieee8023). Data have been collected from public sources as well as through indirect collection from hospitals and physicians. + +We are providing lung bounding boxes of those publicly available datasets. + +--- + +## About the Dataset + +This dataset is a total collection of 616 images with Lung Bounding Boxes of Chest X-ray Dataset of Novel Coronavirus (COVID-19) Cases. The annotation file is in COCO format. + +Each annotation contains two lung bounding boxes (Left Lung, Right Lung) with additional tags such as Finding, Modality, Sex, Survival, View. Each image was manually annotated by qualified radiologists. + +**Warning:** Do not claim diagnostic performance of a model without a clinical study! + +--- + +## Download the Dataset + +### Download the dataset as zip format + + + +### Download using git clone + +Open terminal and run the following command: + +``` +git clone https://github.com/GeneralBlockchain/covid-19-chest-xray-lung-bounding-boxes-dataset.git +``` + +## Links and References + +- Dataset homepage: https://github.com/GeneralBlockchain/covid-19-chest-xray-lung-bounding-boxes-dataset + +- Repository: https://github.com/GeneralBlockchain/covid-19-chest-xray-lung-bounding-boxes-dataset.git + +- Issue tracker: https://github.com/GeneralBlockchain/covid-19-chest-xray-lung-bounding-boxes-dataset/issues + +- Image source: https://github.com/ieee8023/covid-chestxray-dataset +<!-- +- Joseph Paul Cohen, Paul Morrison, Lan Dao, "COVID-19 Image Data Collection" - [paper](https://arxiv.org/abs/2003.11597) +--> +<!-- +- Joseph Paul Cohen, Paul Morrison, Lan Dao, Karsten Roth, Tim Q Duong, Marzyeh Ghassemi, "COVID-19 Image Data Collection: Prospective Predictions Are the Future" - [paper](https://arxiv.org/abs/2006.11988) +--> +- In case of any help you may need from us, please [contact us](#contact-us) directly without any hesitation! We will be glad to help you. + +--- + +## Who are we + +We are **[General Blockchain Inc](https://www.generalblockchain.com/)**, a company developing technology to support the AI industry using blockchain technology. + +Our vision is to build a programmable, human based, artificial intelligence. + +The first application of this human computer is to provide image annotation services to the machine learning and artificial intelligence community. + +Please access our Image Annotation AI services [here](https://www.imageannotation.ai/), today. + +--- + +## Contact Us + +* Email: contact@generalblockchain.com + +--- + +## License + +Each image has license specified in the [metadata.csv](https://github.com/GeneralBlockchain/covid-19-chest-xray-lung-bounding-boxes-dataset/blob/master/metadata.csv) file. Including Apache 2.0, CC BY-NC-SA 4.0, CC BY 4.0. + +The repository is licensed under [Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/). + +--- + +### Special thanks to the following radiologists who worked to the best of their ability to make our research possible: + +Dr. Ayoub El Hajjami + +Dr. Mohamed Soliman + +--- + + +