The RSNA plans to build a COVID-19 imaging data repository, adding to its body of research and education resources for the disease.
The COVID-19 Imaging Data Repository will be an open resource that consists of images and data from institutions, practices, and societies around the world, the RSNA said. An image hosting, annotation, and analysis framework will allow users to track the disease's epidemiological trends and generate new artificial intelligence (AI) algorithms to help detect it, differentiate it from other pneumonias, and plan treatment.
The data repository will be developed in collaboration with the European Imaging COVID-19 AI initiative, which is supported by the European Society of Medical Imaging Informatics.
The society is requesting that COVID-19 imaging data be submitted via a survey by April 15.
![Images show the pectoralis muscles of a healthy male individual who never smoked (age, 66 years; height, 178 cm; body mass index [BMI, calculated as weight in kilograms divided by height in meters squared], 28.4; number of cigarette pack-years, 0; forced expiratory volume in 1 second [FEV1], 97.6% predicted; FEV1: forced vital capacity [FVC] ratio, 0.71; pectoralis muscle area [PMA], 59.4 cm2; pectoralis muscle volume [PMV], 764 cm3) and a male individual with a smoking history and chronic obstructive pulmonary disorder (COPD) (age, 66 years; height, 178 cm; BMI, 27.5; number of cigarette pack-years, 43.2, FEV1, 48% predicted; FEV1:FVC, 0.56; PMA, 35 cm2; PMV, 480.8 cm3) from the Canadian Cohort Obstructive Lung Disease (i.e., CanCOLD) study. The CT image is shown in the axial plane. The PMV is automatically extracted using the developed deep learning model and overlayed onto the lungs for visual clarity.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/03/genkin.25LqljVF0y.jpg?auto=format%2Ccompress&crop=focalpoint&dpr=2&fit=crop&h=167&q=70&w=250)
