Automated lung segmentation from CT images of normal and COVID-19 pneumonia patients

Understand

Automated semantic image segmentation is an essential step in quantitative image analysis and disease diagnosis.

• This study investigates the performance of a deep learning-based model for lung segmentation from CT images for normal and COVID-19 patients.
• Chest CT images and corresponding lung masks of 1200 confirmed COVID-19 cases were used for training a residual neural network.
• The reference lung masks were generated through semi-automated/manual segmentation of the CT images.