Automatic Artery-Vein Separation from Thoracic CT Images Using Integer Programming View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2015-11-20

AUTHORS

Christian Payer , Michael Pienn , Zoltán Bálint , Andrea Olschewski , Horst Olschewski , Martin Urschler

ABSTRACT

Automated computer-aided analysis of lung vessels has shown to yield promising results for non-invasive diagnosis of lung diseases. In order to detect vascular changes affecting arteries and veins differently, an algorithm capable of identifying these two compartments is needed. We propose a fully automatic algorithm that separates arteries and veins in thoracic computed tomography (CT) images based on two integer programs. The first extracts multiple subtrees inside a graph of vessel paths. The second labels each tree as either artery or vein by maximizing both, the contact surface in their Voronoi diagram, and a measure based on closeness to accompanying bronchi. We evaluate the performance of our automatic algorithm on 10 manual segmentations of arterial and venous trees from patients with and without pulmonary vascular disease, achieving an average voxel based overlap of 94.1% (range: 85.0% – 98.7%), outperforming a recent state-of-the-art interactive method. More... »

PAGES

36-43

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-24571-3_5

DOI

http://dx.doi.org/10.1007/978-3-319-24571-3_5

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1034371079


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