Abstract
This work aims at a deep learning-based prediction of wall shear stresses (WSS) for intracranial aneurysms. Based on real patient cases, we created artificial surface models of bifurcation aneurysms. After simulation and WSS extraction, these models were used for training a deep neural network. The trained neural network for 3D mesh segmentation was able to predict areas of high wall shear stress.
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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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Niemann, A., Schneider, L., Preim, B., Voß, S., Berg, P., Saalfeld, S. (2021). Towards Deep Learning-based Wall Shear Stress Prediction for Intracranial Aneurysms. 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_25
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DOI: https://doi.org/10.1007/978-3-658-33198-6_25
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