A cloud-based AI tool for non-contrast chest CT, icolung provides fast and objective quantification of lung involvement in COVID-19 patients to support risk assessment and severity scoring. It enhances diagnostic performance with the aid of deep-learning-based probability scoring, and improves risk assessment with fast and objective quantification of disease burden in COVID-19 patients.
icolung assigns COVID-19 probability to CT images to support diagnosis by increasing sensitivity and specificity of CT imaging.
Increase sensitivity and specificity of CT imaging with AI.
Fast, objective, and standardized quantification of lung involvement to support severity scoring and triage.
Make better-informed treatment decisions through higher specificity for outcome prediction.
Achieve faster radiological reporting on pulmonary status, and improve resource allocation through better patient triage.
Deep-learning image classification with COVID-19 probability score.
Fully automated image segmentation and quantification.
Fast and objective assessment of lesion burden.
Volumetrics per lobe and in total lungs.
Quantification per type of CT finding.
“At the beginning of the COVID-19 pandemic, we received many collaboration requests from universities and companies worldwide. Among them, icometrix stood out to us. They are well known for their neurological solutions and have the expertise and knowledge to provide value to hospitals through AI.”
Dr. Oyunaa von Stackelberg, Head of Research and policy, Diagnostic and Interventional Radiology, University Hospital Heidelberg
“icolung is very accurate and we like the possibility of scrolling through the segmented volumes.”
Marco Nicolò, Radiographer, ASST degli Spedali Civili Brescia