2010 | OriginalPaper | Buchkapitel
Multi-scale Topo-morphometric Opening of Arteries and Veins: An Evaluative Study via Pulmonary CT Imaging
verfasst von : Zhiyun Gao, Colin Holtze, Randall Grout, Milan Sonka, Eric Hoffman, Punam K. Saha
Erschienen in: Advances in Visual Computing
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
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.