Vascular Network Formation in Silico Using the Extended Cellular Potts Model

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F16%3A00087993" target="_blank" >RIV/00216224:14330/16:00087993 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/ICIP.2016.7532946" target="_blank" >http://dx.doi.org/10.1109/ICIP.2016.7532946</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ICIP.2016.7532946" target="_blank" >10.1109/ICIP.2016.7532946</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Vascular Network Formation in Silico Using the Extended Cellular Potts Model

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Vascular Network Formation in Silico Using the Extended Cellular Potts Model

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

—

Projekt

<a href="/cs/project/GA14-22461S" target="_blank" >GA14-22461S: Vývoj a studium metod pro kvantifikaci živých buněk</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2016 IEEE International Conference on Image Processing

ISBN

9781467399616

ISSN

1522-4880

e-ISSN

—

Počet stran výsledku

4

Strana od-do

3180-3183

Název nakladatele

IEEE Signal Processing Society

Místo vydání

Piscataway, NJ, USA

Místo konání akce

Phoenix, USA

Datum konání akce

1. 1. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000390782003040