Distinguishing pulmonary arterial and venous (A/V) trees via in vivo imaging is essential for quantification of vascular geometry useful to diagnose several pulmonary diseases. A multi-scale topo-morphologic opening algorithm has recently been introduced separating A/V trees via non-contrast CT imaging. The method starts with two sets of seeds - one for each of A/V trees and combines fuzzy distance transform, fuzzy connectivity, and morphologic reconstruction leading to locally-adaptive multi-scale opening of two mutually fused structures. Here, we present results of a comprehensive validation study assessing both reproducibility and accuracy of the method. Accuracy of the method is examined using both mathematical phantoms and CT images of contrast-separated pulmonary A/V casting of a pig's lung. Reproducibility of the method is evaluated using multi-user A/V separations of patients's CT pulmonary data and contrast-enhanced CT data of a pig's lung at different volumes. The qualitative and quantitative results are very promising. © 2010 Springer-Verlag.
CITATION STYLE
Gao, Z., Holtze, C., Grout, R., Sonka, M., Hoffman, E., & Saha, P. K. (2010). Multi-scale topo-morphometric opening of arteries and veins: An evaluative study via pulmonary CT imaging. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6455 LNCS, pp. 129–138). https://doi.org/10.1007/978-3-642-17277-9_14
Mendeley helps you to discover research relevant for your work.