Abstract
Mass transport within an organ is complex process which occurs through two different domains: networks of blood vessels and surrounding tissue. Consequently, development of a comprehensive transport model remains a challenge. In this paper we showed an application of a recently introduced multi-scale transport model [1, 2], where larger vessels are modeled by simple 1D finite elements. This model couples convective and diffusive transport within complex system consisted of capillaries and tissue, where connection between these fluid (capillaries) and solid (tissue) domains is accomplished by using fictitious 1D elements. In order to apply the developed model, a reconstruction procedure, consisted of: segmentation, skeletonization using augmented FMM method, and diameter recognition within indoor software, is processed. At the end, numerical simulations are performed in order to get the pressure and concentration distribution in the vessel network and surrounding tissue, showed by examples presented in the paper.
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Acknowledgments
This work was supported in part by the Houston Methodist Research Institute, Ministry of Education and Science of Serbia, grants OI 174028 and III 41007, and City of Kragujevac.
We acknowledge professor Mauro Ferrari from HMRI for overall leadership and guidance, Dr. Eugene Koay from MD Anderson Cancer Center and Sara Errani from HMRI for providing CT images of pancreas and liver.
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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Milosevic, M., Simic, V., Kojic, M. (2018). Numerical Modeling of Drug Delivery in Organs: From CT Scans to FE Model. In: Oliver, N., Serino, S., Matic, A., Cipresso, P., Filipovic, N., Gavrilovska, L. (eds) Pervasive Computing Paradigms for Mental Health. FABULOUS MindCare IIOT 2016 2016 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 207. Springer, Cham. https://doi.org/10.1007/978-3-319-74935-8_12
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DOI: https://doi.org/10.1007/978-3-319-74935-8_12
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