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

Christian Payer, Michael Pienn, Zoltan Balint, Andrea Olschewski, Horst Olschewski, Martin Urschler

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


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.
Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention -- MICCAI 2015
Subtitle of host publication18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part II
EditorsNassir Navab, Joachim Hornegger, William M. Wells, Alejandro F. Frangi
PublisherSpringer International Publishing AG
ISBN (Electronic)978-3-319-24571-3
ISBN (Print)978-3-319-24570-6
Publication statusPublished - 2015

Publication series

NameLecture Notes in Computer Science

Fields of Expertise

  • Information, Communication & Computing

Treatment code (Nähere Zuordnung)

  • Basic - Fundamental (Grundlagenforschung)


  • BioTechMed-Graz


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