SVOBODA, David, Tereza NEČASOVÁ, Lenka TESAŘOVÁ and Pavel ŠIMARA. Tubular Network Formation Process Using 3D Cellular Potts Model. Online. In Gooya A., Goksel O., Oguz I., Burgos N. Simulation and Synthesis in Medical Imaging. LNCS 11037. Neuveden: Springer, 2018. p. 90-99. ISBN 978-3-030-00535-1. Available from: https://dx.doi.org/10.1007/978-3-030-00536-8_10. [citováno 2024-04-24]
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Basic information
Original name Tubular Network Formation Process Using 3D Cellular Potts Model
Authors SVOBODA, David (203 Czech Republic, guarantor, belonging to the institution), Tereza NEČASOVÁ (203 Czech Republic, belonging to the institution), Lenka TESAŘOVÁ (203 Czech Republic, belonging to the institution) and Pavel ŠIMARA (203 Czech Republic, belonging to the institution)
Edition LNCS 11037. Neuveden, Simulation and Synthesis in Medical Imaging, p. 90-99, 10 pp. 2018.
Publisher Springer
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Germany
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
WWW URL
Impact factor Impact factor: 0.402 in 2005
RIV identification code RIV/00216224:14330/18:00101094
Organization unit Faculty of Informatics
ISBN 978-3-030-00535-1
ISSN 0302-9743
Doi http://dx.doi.org/10.1007/978-3-030-00536-8_10
UT WoS 000477752900010
Keywords in English 3D cellular Potts model; Virtual cell; Volumetric image data; Network formation; Fractal dimension; Lacunarity
Tags cbia-web
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 13/5/2020 19:12.
Abstract
The simulations in biomedical imaging serve when the real image data are difficult to be annotated or if they are of limited quantity. An increasing capability of contemporary computers allows to model and simulate complex shapes and dynamic processes. In this paper, we introduce a new model that describes the formation process of a complex tubular network of endothelial cells in 3D. This model adopts the fundamentals of cellular Potts model. The generated network of endothelial cells imitates the structure and behavior that can be observed in real microscopy images. The generated data may serve as a benchmark dataset for newly designed tracking algorithms. Last but not least, the observation of both real and synthetic time-lapse sequences may help the biologists to better understand and model the dynamic processes that occur in live cells.
Links
GA17-05048S, research and development projectName: Segmentace a trekování živých buněk v multimodálních obrazech
Investor: Czech Science Foundation
MUNI/A/0854/2017, interní kód MUName: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace VII.
Investor: Masaryk University, Category A
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