A new software tool that reveals the severity of lung infections in COVID-19 patients has been developed by researchers from the Departments of Computational and Data Science (CDS) and Instrumentation and Applied Physics at the Indian Institute of Science (IISc), in collaboration with colleagues from the Oslo University Hospital and the University of Agder in Norway.

The software tool, which is freely available to the public, has been described in a recent study published in the journal IEEE Transactions on Neural Networks and Learning Systems.

While it is known that COVID-19 can cause severe damage to the respiratory systems, and methods such as X-ray or CT scans can prove helpful in determining how bad the infection is, an IISc release said that the software tool, called AnamNet, can ‘read’ the chest CT scans of COVID-19 patients and estimate how much damage has been caused in the lungs by searching for specific abnormal features. Such a tool can provide automated assistance to doctors and help in faster diagnosis and better management of COVID-19.

“AnamNet employs deep learning and other image processing techniques, which have now become integral to biomedical research and applications. The software can identify infected areas in a chest CT scan with a high degree of accuracy,” the release explained.

A sample demo of the tool can be found on: https://github.com/NaveenPaluru/Segmentation-COVID-19.

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