Respiratory Infectious Diseases Imaging AI Registry
Team: Lucian Beer, Benedikt Heidinger, Tanja Eichner, Jeanny Pan, Matthias Perkonigg, Sebastian Röhrich, Helmut Prosch, Georg Langs
Objectives: RIFTAIR is a registry study to collect imaging data and relevant clinical data of patients with infectious lung diseases who have undergone CT examinations. Data collection includes data from before the ongoing COVID-19 pandemic, and continues as a prospective study.
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Please contact us: email
Code
Code and models for automatic lung segmentation in CT data used by many others by now (Hofmanninger et al. 2020): code github
Relevant publications by project members:
- Heidinger, B.H., Kifjak, D., Prayer, F., Beer, L., Milos, R.I., Röhrich, S., Arndt, H. and Prosch, H., 2020. Radiological manifestations of pulmonary diseases in COVID-19. Der Radiologe.
- Revel, M.P., Parkar, A.P., Prosch, H., Silva, M., Sverzellati, N., Gleeson, F. and Brady, A., 2020. COVID-19 patients and the Radiology department–advice from the European Society of Radiology (ESR) and the European Society of Thoracic Imaging (ESTI). European radiology, 30(9), pp.4903-4909.
- Lang, C., Jaksch, P., Hoda, M.A., Lang, G., Staudinger, T., Tschernko, E., Zapletal, B., Geleff, S., Prosch, H., Gawish, R. and Knapp, S., 2020. Lung transplantation for COVID-19-associated acute respiratory distress syndrome in a PCR-positive patient. The Lancet Respiratory Medicine, 8(10), pp.1057-1060.
- Roberts, M., Driggs, D., Thorpe, M., Gilbey, J., Yeung, M., Ursprung, S., Aviles-Rivero, A.I., Etmann, C., McCague, C., Beer, L. and Weir-McCall, J.R., 2021. Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans. Nature Machine Intelligence, 3(3), pp.199-217.
- Hofmanninger, J., Prayer, F., Pan, J., Röhrich, S., Prosch, H. and Langs, G., 2020. Automatic lung segmentation in routine imaging is primarily a data diversity problem, not a methodology problem. European Radiology Experimental, 4(1), pp.1-13.
- Röhrich, S., Hofmanninger, J., Negrin, L., Langs, G. and Prosch, H., 2021. Radiomics score predicts acute respiratory distress syndrome based on the initial CT scan after trauma. European Radiology, pp.1-11.
- Röhrich, S., Hofmanninger, J., Prayer, F., Müller, H., Prosch, H. and Langs, G., 2020. Prospects and Challenges of Radiomics by Using Nononcologic Routine Chest CT. Radiology: Cardiothoracic Imaging, 2(4), p.e190190.