Using artificial intelligence to detect Covid-19 in X-rays

Posted on 27 May 2020 by Jonny Williamson

Students at Cranfield University specialising in Computer and Machine Vision (CMV) have designed intelligent computer models that can identify Covid-19 in X-rays.

A common symptom of Covid-19 is pneumonia. Being able to detect pneumonia-related anomalies in an X-ray, therefore, could aid in the tracking of the virus.

Two groups studying for their MSc programme at Cranfield University decided to take up the challenge as their group project, which tasked the students to work collaboratively on problems and to devise a solution.

The groups created two models which use computer vision and artificial intelligence (AI) to analyse chest X-ray imagery. It can classify information which would not normally be recognised with the naked eye and assist with the diagnosis of Covid-19.

The first model classifies anomalies which are positive for pneumonia, then a second model is used to diagnose if the pneumonia is caused by the Covid-19 virus.

The lack of X-ray imagery in the public domain containing relevant details was a challenge; however, the teams were able to build detailed information from various sources.

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 reportedly able to predict results to a high degree of accuracy. However, the research teams believe that they are able to further develop new algorithms to produce even more robust and reliable results.

The groups were themselves impacted by Covdi-19, due to lockdown, and some students returned to their homes overseas. The determined groups continued with their projects remotely, despite being thousands of miles apart in China and France, as well as Cranfield and Milton Keynes.

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 project to the next level, using more advanced AI algorithms and CT (computed tomography) scans to show greater detail and accuracy in the results.

Dr Rana commented: “The research carried out in this pilot project has led to some extremely promising results and we are looking to build on this success rapidly to help in the fight against Covid-19.”

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