The CADCOVID-19 project aims to develop an online system to assist in the diagnosis of COVID-19 using artificial intelligence and computer vision techniques.
This is not another generic project trying to apply deep learning for covid-19 diagnosis. The ideia is to create a system based on a novel technology developed in our lab called Conditional Domain Adaptation Generative Adversarial Networks (CoDAGANs). CODAGANs are very effective in learning to segment from multiple image domains.
Official webpage of the project: http://www.cadcovid19.dcc.ufmg.br/
Products:
- Lung Diseases Recognition Tool: http://www.cadcovid19.dcc.ufmg.br/classification
Related Publications:
- Oliveira, H. N., Ferreira, E., & Dos Santos, J. A. (2020). Truly generalizable radiograph segmentation with conditional domain adaptation. IEEE Access, 8, 84037-84062. [PDF]
- Oliveira, H., Mota, V., Machado, A. M., & dos Santos, J. A. (2020). From 3D to 2D: Transferring knowledge for rib segmentation in chest X-rays. Pattern Recognition Letters, 140, 10-17. [PDF]