Medical 3D imaging company Coreline Soft has received approval from the South Korea Ministry of Food and Drug Safety for its computer-aided detection (CAD) software that helps screen for cancerous lung nodules.
The Aview Lung Nodule CAD software uses artificial intelligence to identify pulmonary nodules on CT scans. The CAD solution is designed to work with the company's Aview product line, which includes the Aview LCS lung cancer screening software.
In a clinical trial, Coreline's CAD solution achieved a 97% nodule detection rate, according to the company. The vendor is preparing to submit its CAD solution for approval in the U.S. and European Union.
Coreline also announced that Aview was selected for the fourth year as the software solution for South Korea's National Lung Screening Trial, a multisociety effort exploring the feasibility of population-based lung cancer screening. The company will also provide solutions for a large-scale lung cancer screening trial taking place in six European countries.
![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)
