Multi-scale Topo-morphometric Opening of Arteries and Veins: An Evaluative Study via Pulmonary CT Imaging

Abstract

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.