Three-dimensional synthetic blood vessels generation using stochastic Lindenmayer systems.

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Magnetic resonance angiography (MRA) or computed tomography angiography (CTA) images allow for a thorough analysis of the blood vessels. Vessel segmentation from MRA or CTA is thus the primary task in the diagnosis of vascular diseases such as stenosis and aneurysms. The wide architectural variability of the blood vessels, however, hinders the validation of vascular segmentation methods. The construction of synthetic realistic vascular architecture trees will aid in the validation of new vessel segmentation methodologies. This thesis describes a three-dimensional synthetic blood vessel generation methodology that employs stochastic Lindenmayer systems (L-systems). For this purpose, we implemented a parser and a generator of L-systems to create grammars that represent blood vessel architectures. The parameterization of the grammar allows one to simulate natural features of real vessels such as bifurcation angle, average length and diameter, and also accounts for vascular anomalies. The resulting expressions are used to create synthetic angiographic images that mimic real vessel intensity distributions in MRA and CTA. Blood vessel growth can also be delimited by arbitrary 3D surfaces that may represent organ geometries. The flexibility in the parameterization and stochastic nature of this methodology makes it an ideal tool for the validation of blood vessel segmentation algorithms from angiographic images.

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November 09, 2012
Room 256, block A
Cidade Universitária
São Paulo
Miguel Angel Galarreta Valverde
Prof. Dr. Jackowski, Marcel Parolin
Theses USP
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