Pulmonary Structure

Pulmonary structure research focuses on accurately segmenting and analyzing key anatomical features in the lungs, such as airways, vessels, fissures, and lesions (e.g., ground-glass opacities and consolidations), from medical images like CT scans. Current research employs advanced deep learning techniques, including multitask learning and post-processing methods for topology repair, to improve segmentation accuracy and address challenges like disconnectivity in automated analyses. These advancements are crucial for improving the diagnosis and treatment of pulmonary diseases, enabling more precise and efficient clinical workflows. The development of publicly available datasets and open-source tools further facilitates progress in this vital area.