Student team develops tool for diagnosing COVID-19 from X-rays

The models use computer vision and artificial intelligence (AI) to analyse chest X-ray imagery for signs of pneumonia - a common symptom of COVID-19 - and to determine whether this is caused by the COVID-19 virus.

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The technology has been developed by two groups studying for their MSc programme, specialising in Computer and Machine Vision. Due to lockdown, the groups carried out the projects remotely, and were able to use video conference and IT facilities provided by the University to access the computational resources required.

The groups employed conventional machine learning algorithms as well as deep learning frameworks, a machine learning technique that teaches computers to learn by example. The AI model employed in this project was able to predict results with great accuracy. However, the research teams believe that they can further develop new algorithms to produce even more robust and reliable results.

The teams are led by Dr Zeeshan Rana, Lecturer in Computational Engineering at Cranfield University. He is now exploring collaboration opportunities with medical authorities or industry to develop the Covid-19 x-rays project to the next level, using more advanced AI algorithms and CT (computed tomography) scans to show greater detail and accuracy in the results.