Silicosis is a form of an occupational lung disease caused by the inhalation of crystalline silica dust. The lung disease is often characterizen by shortness of breath, cough and fever, and often misdiagnosed as pulmonary edema, pneumonia and tuberculosis. Because silicosis affects the immune system, it also increases the risk of lung infections, such as tuberculosis.

The Computer-Aided Detection for Tuberculosis software (CAD4TB) has screened close to 10 million people in over 40 countries, and was recently endorsed by the World Health Organisation to support screening and triage of tuberculosis. Now, building on the robust technical instrastructure of CAD4TB, Delft Imaging developed CAD4Silicosis – Computer Aided Detection software that uses artifical intelligence to detect abnormalities related to the lung disease silicosis.

Like with CAD4TB, the CAD4Silicosis software scores a digital X-ray image between 0 and 100, with recommended thresholds and can be deployed via the Cloud.. Moreover, it is also the only artificial intelligence-based tool that is able to select either silicosis or silicotuberculosis among no-silicosis chest X-ray images (normal and TB). CAD4Silicosis can be deployed using the cloud.

Late 2019, a publication in The International Journal of Tuberculosis and Lung Health by Young et al. already presented findings from a study of the use of computer-aided detection of TB and silicosis in a group of southern Africa gold miners. The study used four computer-aided detection systems (incl. CAD4Silicosis) to detect silicosis, TB and silicotuberculosis using expert-determine classifications and found better than expected sensitivities and specificities within these CAD systems. The study revealed the potential for a CAD system to rapidly screen out chest radiographs with no abnormalities, allowing for much higher throughput in screening.

For more information on CAD4Silicosis and how to access it, please reach out to