Brunel Uni uses image analytics to spot viruses in lungs

Researchers at Brunel University London have used image analytics to accurately spot Covid-19, SARS and MERS on patients’ lungs. Such analytics can be used to work out what to look for in X-rays and spot signs of disease, and then with the help of deep learning, the disease identified can be specifically classified to help with diagnosis, a clear additional support to any radiology department. The researchers hope that their image analytics will have further implications by being able to spot signs of other lung diseases like pneumonia, asthma and lung cancer.

Professor of Electronics and Computer Engineering at Brunel University, Abdul Sadka, said: “New techniques in image analytics and AI can, and should, play an instrumental role in restraining the spread of COVID-19. By automatically and accurately identifying the disease. With the virus not going away anytime soon, this technology has the capability to massively ramp up our response to the disease and enable the healthcare specialists to identify, monitor and handle the treatment of pulmonary diseases. What is needed now is for the business sector to come forward and help get it out to the NHS as soon as practically possible.”