AZmed has received the CE mark for AZnod, designed to detect and characterize pulmonary nodules on CT scans.
AZnod is the first AI tool for CT within AZmed’s Rayscan product line, extending the firm’s Rayvolve AI suite beyond x-rays. It is designed to aid lung cancer screening programs by providing standardized detection and comprehensive characterization of pulmonary nodules on CT scans. The software identifies and evaluates nodules between 3 mm and 30 mm, providing measurements of volume, long-axis diameter, and perpendicular diameters, as well as indicating the exact CT slices on which they are present.
The tool classifies the nodules according to density, contour morphology, internal composition, and position in the lungs, and generates a report listing each nodule by clinical priority. The report includes annotated views of size and standardized measurements in millimeters and cubic millimeters, and the nodules’ diagnostic attributes, as well as an anatomical lung schematic to assist with assessment of the nodules, AZmed added.
















![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&fit=crop&h=112&q=70&w=112)



