Tubular Network Formation Process Using 3D Cellular Potts Model

D 2018

Tubular Network Formation Process Using 3D Cellular Potts Model

SVOBODA, David, Tereza NEČASOVÁ, Lenka TESAŘOVÁ and Pavel ŠIMARA

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

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Germany

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

References:

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

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

Abstract

V originále

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 project

Name: Segmentace a trekování živých buněk v multimodálních obrazech

Investor: Czech Science Foundation

MUNI/A/0854/2017, interní kód MU

Name: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace VII.

Investor: Masaryk University, Category A

Citovat

SVOBODA, David, Tereza NEČASOVÁ, Lenka TESAŘOVÁ and Pavel ŠIMARA. Tubular Network Formation Process Using 3D Cellular Potts Model. 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.

@inproceedings{1426797,
   author = {Svoboda, David and Nečasová, Tereza and Tesařová, Lenka and Šimara, Pavel},
   address = {Neuveden},
   booktitle = {Simulation and Synthesis in Medical Imaging},
   doi = {http://dx.doi.org/10.1007/978-3-030-00536-8_10},
   edition = {LNCS 11037},
   editor = {Gooya A., Goksel O., Oguz I., Burgos N.},
   keywords = {3D cellular Potts model; Virtual cell; Volumetric image data; Network formation; Fractal dimension; Lacunarity},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Neuveden},
   isbn = {978-3-030-00535-1},
   pages = {90-99},
   publisher = {Springer},
   title = {Tubular Network Formation Process Using 3D Cellular Potts Model},
   url = {http://www.sashimi.aramislab.fr/},
   year = {2018}
}

TY  - JOUR
ID  - 1426797
AU  - Svoboda, David - Nečasová, Tereza - Tesařová, Lenka - Šimara, Pavel
PY  - 2018
TI  - Tubular Network Formation Process Using 3D Cellular Potts Model
PB  - Springer
CY  - Neuveden
SN  - 9783030005351
KW  - 3D cellular Potts model
KW  - Virtual cell
KW  - Volumetric image data
KW  - Network formation
KW  - Fractal dimension
KW  - Lacunarity
UR  - http://www.sashimi.aramislab.fr/
N2  - 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.
ER  -

SVOBODA, David, Tereza NEČASOVÁ, Lenka TESAŘOVÁ and Pavel ŠIMARA. Tubular Network Formation Process Using 3D Cellular Potts Model. In Gooya A., Goksel O., Oguz I., Burgos N. \textit{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.

Detailed Information on Publication Record