Software tool to diagnose Covid-19 lung infection | Bangalore News


BENGALURU: A team led by IISc researchers has developed a software tool that reveals the severity of lung infections in Covid-19 patients.
Called AnamNet, the software tool can ‘read’ chest CT scans of potential Covid-19 patients and estimate damage to the lungs by looking for specific abnormal features. It can provide automated assistance to doctors and therefore help in faster diagnosis and better management of Covid-19.
AnamNet was developed by researchers from the Departments of Computing and Data Science (CDS) and Instrumentation and Applied Physics in collaboration with researchers from the University Hospital of Oslo and the University of Agder in Norway. . The study was published in the journal IEEE Transactions on Neural Networks and Learning Systems.
The software uses deep learning and other image processing techniques. Researchers trained Anam-Net to look for abnormalities and classify areas on the lung scan as infected or not. The tool can accurately assess the severity of the disease by comparing an infected area with a healthy area.
Naveen Paluru, lead author and doctoral student in the lab of Phaneendra Yalavarthy, Associate Professor, CDS, said: “It essentially extracts features from chest CT images and projects them into non-linear space. [a mathematical representation], then recreate the [segmented] image of this representation.
The software is lightweight with a small memory footprint. The team has developed an app called CovSeg that can be run on a mobile phone and potentially used by healthcare professionals. Paluru claims this feature is missing from the cutting edge technologies currently available that require specialized hardware.
The software tool is available free to the public.


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