An Efficient Approach to Pulmonary Vessels Extraction Based on Curve Evolution

Pulmonary vessels extraction is a challenging task in clinical medicine. Many pulmonary diseases are accompanied by the changes of vessel diameters. The vessels and their branches, which exhibit much variability, are most important in performing diagnosis and planning the follow-up therapies. In this paper, we propose an efficient approach to pulmonary vessels extraction based on the curve evolution. This approach models the vessels as monotonically marching front under the speed field integrating both the region and the edge information where a new region speed function is designed and integrated with the edge based speed function. Due to the region based speed term, the front could even propagate in small narrow vessel branches. To further improve the segmentation results, a multi-initial fast marching algorithm is developed to fast implement the numerical solution, which may avoid the monotonically marching front leaking out of the weak boundary too earlier and also reduce the computational cost. The validity of our approach is demonstrated by CT pulmonary vessels extraction. Experiments show that the segmentation results by our approach, especially on the narrow thin vessel branches extraction, are more precise than that of the existing method.