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@inproceedings{1348198,
author = {Svoboda, David and Ulman, Vladimír and Kováč, Peter and Šalingová, Barbara and Tesařová, Lenka and Krontorád Koutná, Irena and Matula, Petr},
address = {Piscataway, NJ, USA},
booktitle = {2016 IEEE International Conference on Image Processing},
doi = {http://dx.doi.org/10.1109/ICIP.2016.7532946},
keywords = {Synthetic image formation; Vascular network; Cellular Potts model; Angiogenesis},
howpublished = {paměťový nosič},
language = {eng},
location = {Piscataway, NJ, USA},
isbn = {978-1-4673-9961-6},
pages = {3180-3183},
publisher = {IEEE Signal Processing Society},
title = {Vascular Network Formation in Silico Using the Extended Cellular Potts Model},
url = {http://dx.doi.org/10.1109/ICIP.2016.7532946},
year = {2016}
}
TY - JOUR
ID - 1348198
AU - Svoboda, David - Ulman, Vladimír - Kováč, Peter - Šalingová, Barbara - Tesařová, Lenka - Krontorád Koutná, Irena - Matula, Petr
PY - 2016
TI - Vascular Network Formation in Silico Using the Extended Cellular Potts Model
PB - IEEE Signal Processing Society
CY - Piscataway, NJ, USA
SN - 9781467399616
KW - Synthetic image formation
KW - Vascular network
KW - Cellular Potts model
KW - Angiogenesis
UR - http://dx.doi.org/10.1109/ICIP.2016.7532946
N2 - Cardiovascular diseases belong to the most widespread illnesses in the developed countries. Therefore, the regenerative medicine and tissue modeling applications are highly interested in studying the ability of endothelial cells, derived from human stem cells, to form vascular networks. Several characteristics can be measured on images of these networks and hence describe the quality of the endothelial cells. With advances in the image processing, automatic analysis of these complex images becomes increasingly common. In this study, we introduce a new graph structure and additional constraints to the cellular Potts model, a framework commonly utilized in computational biology. Our extension allows to generate visually plausible synthetic image sequences of evolving fluorescently labeled vascular networks with ground truth data. Such generated datasets can be subsequently used for testing and validating methods employed for the analysis and measurement of the images of real vascular networks.
ER -
SVOBODA, David, Vladimír ULMAN, Peter KOVÁČ, Barbara ŠALINGOVÁ, Lenka TESAŘOVÁ, Irena KRONTORÁD KOUTNÁ and Petr MATULA. Vascular Network Formation in Silico Using the Extended Cellular Potts Model. In \textit{2016 IEEE International Conference on Image Processing}. Piscataway, NJ, USA: IEEE Signal Processing Society, 2016, p.~3180-3183. ISBN~978-1-4673-9961-6. Available from: https://dx.doi.org/10.1109/ICIP.2016.7532946.
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