Abstract
Computational Fluid Dynamic calculations are a great assistance for rupture prediction of cerebral aneurysms. This procedure requires a consistent surface, as well as a separation of the blood vessel and aneurysm on this surface to calculate rupture-relevant scores. For this purpose we present an automatic pipeline, which generates a surface model of the vascular tree from angiographies determined by a markerbased watershed segmentation and label post-processing. Aneurysms on the surface model are then detected and segmented using shape-based graph cuts along with anisotropic diffusion and an iterative Support Vector Machine based classification. Aneurysms are correctly detected and segmented in 33 out of 35 test cases. Simulation relevant vessels are successfully segmented without vessel merging in 131 out of 144 test cases, achieving an average dice coefficient of 0.901.
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© 2021 Der/die Autor(en), exklusiv lizenziert durch Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature
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Felde, J., Wagner, T., Lamecker, H., Doenitz, C., Gundelwein, L. (2021). Automatic Vessel Segmentation and Aneurysm Detection Pipeline for Numerical Fluid Analysis. In: Palm, C., Deserno, T.M., Handels, H., Maier, A., Maier-Hein, K., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2021. Informatik aktuell. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-33198-6_57
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DOI: https://doi.org/10.1007/978-3-658-33198-6_57
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