Airway Tree

The airway tree, the branching network of tubes carrying air to and from the lungs, is a critical focus of medical imaging research, aiming to improve diagnosis and treatment of respiratory diseases. Current research emphasizes automated segmentation and analysis of airway structures from CT scans using deep learning architectures like U-Net and YOLO, often incorporating attention mechanisms and graph neural networks to enhance accuracy and topological consistency, particularly in challenging cases with pathologies. These advancements enable more precise quantification of airway morphology, facilitating improved disease characterization, intervention planning (e.g., bronchoscopy), and potentially even early disease prediction. The development of large, publicly available datasets with diverse pathologies is driving progress in this field.