Paper
13 March 2006 On the assumption of cubic graphs of vascular networks
Sung-Hyuk Cha, Sukmoon Chang, Michael L. Gargano
Author Affiliations +
Abstract
A vascular network is often represented by a Reeb graph, which is a topological skeleton, and graph theory has been widely applied to analyze properties of a vascular network. A Reeb graph model for a vascular network is obtained by assigning the branch points of the network to be the vertices of the graph and the vessels between branch points to be the edges of the graph. Vascular networks develop by way of angiogenesis, a growth process that involves the biological mechanisms of vessel sprouting (budding) and splitting (intussusception). Vascular networks develop by way of two biological mechanisms of vessel sprouting (budding) and splitting (intussusception). According to a graph theory modeling of two vascular network growth mechanisms, all nodes in the Reeb graph must be cubic in degree except for two special nodes: the afferent (A) and efferent (E) nodes. We define that a vascular network is cubic if all internal nodes are cubic in degree. We consider six normal adult rat renal glomerular networks and use their reeb graphs already constructed and published in the literature. We observe that five of them contain internal vertices of degree higher than three. Branch points in vascular networks may appear to be of a higher degree if the imaging resolution cannot differentiate between blood vessels that are very close in proximity. Here, we propose a random graph theory model that edits a non-cubic vascular network into a cubic graph. We observe that the edited cubic graph from a non-cubic vascular network has the similar size and order as the one cubic vascular network.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sung-Hyuk Cha, Sukmoon Chang, and Michael L. Gargano "On the assumption of cubic graphs of vascular networks", Proc. SPIE 6143, Medical Imaging 2006: Physiology, Function, and Structure from Medical Images, 61432M (13 March 2006); https://doi.org/10.1117/12.648766
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KEYWORDS
Blood vessels

Image resolution

Network security

Blood

Capillaries

Computer science

Image processing

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