27 March 2009 Segmentation of lung vessel trees by global optimization
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Proceedings Volume 7259, Medical Imaging 2009: Image Processing; 725912 (2009) https://doi.org/10.1117/12.811570
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States
Abstract
We present a novel method for lung vessel tree segmentation. The method combines image information and a high-level physiological model, stating that the vasculature is organized such that the whole organ is perfused using minimal effort. The method consists of three consecutive steps. First, a limited set of possible bifurcation locations is determined. Subsequently, individual vessel segments of varying diameters are constructed between each two bifurcation locations. This way, a graph is constructed consisting of each bifurcation location candidate as vertices and vessel segments as edges. Finally, the overall vessel tree is found by selecting the subset of these segments that perfuses the whole organ, while minimizing an energy function. This energy function contains a data term, a volume term and a bifurcation term. The data term measures how well the selected vessel segments fit to the image data, the volume term measures the total amount of blood in the vasculature, and the bifurcation term models the physiological fit of the diameters of the in- and outgoing vessels in each bifurcation. The selection of the optimal subset of vessel segments into a single vessel tree is an NP-hard combinatorial optimization problem that is solved here with an ant colony optimization approach. The bifurcation detection as well as the segmentation method have been validated on lung CT images with manually segmented arteries and veins.
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Pieter Bruyninckx, Dirk Loeckx, Dirk Vandermeulen, Paul Suetens, "Segmentation of lung vessel trees by global optimization", Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 725912 (27 March 2009); doi: 10.1117/12.811570; https://doi.org/10.1117/12.811570
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