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Payer, C; Pienn, M; Bálint, Z; Shekhovtsov, A; Talakic, E; Nagy, E; Olschewski, A; Olschewski, H; Urschler, M.
Automated integer programming based separation of arteries and veins from thoracic CT images.
Med Image Anal. 2016; 34:109-122 Doi: 10.1016/ [OPEN ACCESS]
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Führende Autor*innen der Med Uni Graz
Urschler Martin
Co-Autor*innen der Med Uni Graz
Balint Zoltan
Nagy Eszter
Olschewski Andrea
Olschewski Horst
Pienn Michael
Talakic Emina

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Automated computer-aided analysis of lung vessels has shown to yield promising results for non-invasive diagnosis of lung diseases. To detect vascular changes which affect pulmonary arteries and veins differently, both compartments need to be identified. We present a novel, fully automatic method that separates arteries and veins in thoracic computed tomography images, by combining local as well as global properties of pulmonary vessels. We split the problem into two parts: the extraction of multiple distinct vessel subtrees, and their subsequent labeling into arteries and veins. Subtree extraction is performed with an integer program (IP), based on local vessel geometry. As naively solving this IP is time-consuming, we show how to drastically reduce computational effort by reformulating it as a Markov Random Field. Afterwards, each subtree is labeled as either arterial or venous by a second IP, using two anatomical properties of pulmonary vessels: the uniform distribution of arteries and veins, and the parallel configuration and close proximity of arteries and bronchi. We evaluate algorithm performance by comparing the results with 25 voxel-based manual reference segmentations. On this dataset, we show good performance of the subtree extraction, consisting of very few non-vascular structures (median value: 0.9%) and merged subtrees (median value: 0.6%). The resulting separation of arteries and veins achieves a median voxel-based overlap of 96.3% with the manual reference segmentations, outperforming a state-of-the-art interactive method. In conclusion, our novel approach provides an opportunity to become an integral part of computer aided pulmonary diagnosis, where artery/vein separation is important.
Find related publications in this database (using NLM MeSH Indexing)
Algorithms - administration & dosage
Humans - administration & dosage
Pulmonary Artery - diagnostic imaging
Pulmonary Veins - diagnostic imaging
Thorax - blood supply, diagnostic imaging
Tomography, X-Ray Computed - administration & dosage

Find related publications in this database (Keywords)
Vascular tree reconstruction
Artery-vein separation
Computed tomography
Integer program
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