Issue |
EPJ Web Conf.
Volume 180, 2018
EFM17 – Experimental Fluid Mechanics 2017
|
|
---|---|---|
Article Number | 02092 | |
Number of page(s) | 11 | |
Section | Contributions | |
DOI | https://doi.org/10.1051/epjconf/201818002092 | |
Published online | 04 June 2018 |
https://doi.org/10.1051/epjconf/201818002092
Processing of Cells’ Trajectories Data for Blood Flow Simulation Model*
Cell-in-fluid Research Group, http://cell-in-fluid.fri.uniza.sk; Department of Software Technologies; Faculty of Management Science and Informatics, Žilina, Slovakia
* Supported by the Slovak Research and Development Agency under the contract No. APVV-15-0751, by the Ministry of Education, Science, Research and Sport of the Slovak Republic under the contract No. VEGA 1/0643/17 and by FVG 2017 grant of Faculty of Management Science and Informatics, University of Žilina.
+ Corresponding authors: martin.slavik@fri.uniza.sk, hynek.bachraty@fri.uniza.sk
Published online: 4 June 2018
Simulations of the red blood cells (RBCs) flow as a movement of elastic objects in a fluid, are developed to optimize microfluidic devices used for a blood sample analysis for diagnostic purposes in the medicine. Tracking cell behaviour during simulation helps to improve the model and adjust its parameters. For the optimization of the microfluidic devices, it is also necessary to analyse cell trajectories as well as likelihood and frequency of their occurrence in a particular device area, especially in the parts, where they can affect circulating tumour cells capture. In this article, we propose and verify several ways of processing and analysing the typology and trajectory stability in simulations with single or with a large number of red blood cells (RBCs) in devices with different topologies containing cylindrical obstacles.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.