Datasets
Models
Downloads: 1
Data:
Image
Specialty:
Infectious Diseases
Radiology
Respiratory Medicine
Medical Imaging Technique:
CT
X-Ray
Medical Imaging Region:
Chest
Lungs
Clinical Purpose:
Diagnosis
Task:
Classification
Detection
Risk Stratification
License:
Creative Commons Attribution Non Commercial Share Alike 4.0
Image
Specialty:
Infectious Diseases
Radiology
Respiratory Medicine
Medical Imaging Technique:
CT
X-Ray
Medical Imaging Region:
Chest
Lungs
Clinical Purpose:
Diagnosis
Task:
Classification
Detection
Risk Stratification
License:
Creative Commons Attribution Non Commercial Share Alike 4.0
Switch to unified view
| a/README.md | b/README.md | ||
|---|---|---|---|
... |
... |
||
| 70 | 70 | ||
| 71 | [Generated Lung Segmentations](annotations/lungVAE-masks) (license: CC BY-SA) from the paper [Lung Segmentation from Chest X-rays using Variational Data Imputation](https://arxiv.org/abs/2005.10052) |
71 | [Generated Lung Segmentations](annotations/lungVAE-masks) (license: CC BY-SA) from the paper [Lung Segmentation from Chest X-rays using Variational Data Imputation](https://arxiv.org/abs/2005.10052) |
| 72 | 72 | ||
| 73 | [Brixia score for 192 images](https://github.com/BrixIA/Brixia-score-COVID-19) (license: CC BY-NC-SA) from the paper [End-to-end learning for semiquantitative rating of COVID-19 severity on Chest X-rays](https://arxiv.org/abs/2006.04603) |
73 | [Brixia score for 192 images](https://github.com/BrixIA/Brixia-score-COVID-19) (license: CC BY-NC-SA) from the paper [End-to-end learning for semiquantitative rating of COVID-19 severity on Chest X-rays](https://arxiv.org/abs/2006.04603) |
| 74 | 74 | ||
| 75 | [Lung and other segmentations for 517 images](https://github.com/v7labs/covid-19-xray-dataset/tree/master/annotations) (license: CC BY) in COCO and raster formats by [v7labs](https://github.com/v7labs/covid-19-xray-dataset) |
75 | [Lung and other segmentations for 517 images](https://easymed.ai/datasets/GeorgeSullivan/XRayCovid19/git/ci/main/tree/annotations/) (license: CC BY) in COCO and raster formats by [v7labs](https://easymed.ai/datasets/GeorgeSullivan/XRayCovid19/) |
| 76 | 76 | ||
| 77 | ## Contribute |
77 | ## Contribute |
| 78 | 78 | ||
| 79 | - Submit data directly to the project. View our [research protocol](https://docs.google.com/document/d/14b7cou98YhYcJ2jwOKznChtn5y6-mi9bgjeFv2DxOt0/edit). Contact us to start the process. |
79 | - Submit data directly to the project. View our [research protocol](https://docs.google.com/document/d/14b7cou98YhYcJ2jwOKznChtn5y6-mi9bgjeFv2DxOt0/edit). Contact us to start the process. |
| 80 | - We can extract images from publications. Help identify publications which are not already included using a GitHub issue (DOIs we have are listed in the metadata file). There is a searchable database of COVID-19 papers [here](https://www.who.int/emergencies/diseases/novel-coronavirus-2019/global-research-on-novel-coronavirus-2019-ncov), and a non-searchable one (requires download) [here](https://pages.semanticscholar.org/coronavirus-research). |
80 | - We can extract images from publications. Help identify publications which are not already included using a GitHub issue (DOIs we have are listed in the metadata file). There is a searchable database of COVID-19 papers [here](https://www.who.int/emergencies/diseases/novel-coronavirus-2019/global-research-on-novel-coronavirus-2019-ncov), and a non-searchable one (requires download) [here](https://pages.semanticscholar.org/coronavirus-research). |