Image-based Simulations of Tubular Network Formation

D 2020

Image-based Simulations of Tubular Network Formation

SVOBODA, David and Tereza NEČASOVÁ

Basic information

Original name

Image-based Simulations of Tubular Network Formation

Authors

SVOBODA, David (203 Czech Republic, guarantor, belonging to the institution) and Tereza NEČASOVÁ (203 Czech Republic, belonging to the institution)

Edition

Neuveden, 17th IEEE International Symposium on Biomedical Imaging, p. 1608-1612, 5 pp. 2020

Publisher

IEEE

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

References:

URL

RIV identification code

RIV/00216224:14330/20:00114090

Organization unit

Faculty of Informatics

ISBN

978-1-5386-9330-8

ISSN

DOI

http://dx.doi.org/10.1109/ISBI45749.2020.9098736

UT WoS

000578080300336

Keywords in English

Light Microscopy; Confocal Microscopy; Fluorescence Microscopy; Cells & molecules; Image synthesis

Abstract

V originále

The image-based simulations in biomedicine play an important role as the real image data are difficult to be fully and precisely annotated. An increasing capability of contemporary computers allows to model and simulate reasonably complicated structures and in the last years also the dynamic processes. In this paper, we introduce a complex 3D model that describes the structure and dynamics of the population of endothelial cells. The model is based on standard cellular Potts model. It describes the formation process of a complex tubular network of endothelial cells fully in 3D together with the simulation of the cell death called apoptosis. The generated network imitates the structure and behavior that can be observed in real phase-contrast microscopy. The generated image data may serve as a benchmark dataset for newly designed detection or tracking algorithms.

Links

EF16_013/0001775, research and development project

Name: Modernizace a podpora výzkumných aktivit národní infrastruktury pro biologické a medicínské zobrazování Czech-BioImaging

GA17-05048S, research and development project

Name: Segmentace a trekování živých buněk v multimodálních obrazech

Investor: Czech Science Foundation

LTC17016, research and development project

Name: Benchmarking algoritmů segmentace a sledování buněk

Investor: Ministry of Education, Youth and Sports of the CR, Benchmarking of algorithms for cell segmentation and tracking, INTER-COST

MUNI/A/1050/2019, interní kód MU

Name: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace IX (Acronym: SV-FI MAV IX)

Investor: Masaryk University, Category A

Citovat

SVOBODA, David and Tereza NEČASOVÁ. Image-based Simulations of Tubular Network Formation. Online. In 17th IEEE International Symposium on Biomedical Imaging. Neuveden: IEEE, 2020, p. 1608-1612. ISBN 978-1-5386-9330-8. Available from: https://dx.doi.org/10.1109/ISBI45749.2020.9098736.

@inproceedings{1643137,
   author = {Svoboda, David and Nečasová, Tereza},
   address = {Neuveden},
   booktitle = {17th IEEE International Symposium on Biomedical Imaging},
   doi = {http://dx.doi.org/10.1109/ISBI45749.2020.9098736},
   keywords = {Light Microscopy; Confocal Microscopy; Fluorescence Microscopy; Cells & molecules; Image synthesis},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {Neuveden},
   isbn = {978-1-5386-9330-8},
   pages = {1608-1612},
   publisher = {IEEE},
   title = {Image-based Simulations of Tubular Network Formation},
   url = {http://2020.biomedicalimaging.org/},
   year = {2020}
}

TY  - JOUR
ID  - 1643137
AU  - Svoboda, David - Nečasová, Tereza
PY  - 2020
TI  - Image-based Simulations of Tubular Network Formation
PB  - IEEE
CY  - Neuveden
SN  - 9781538693308
KW  - Light Microscopy
KW  - Confocal Microscopy
KW  - Fluorescence Microscopy
KW  - Cells & molecules
KW  - Image synthesis
UR  - http://2020.biomedicalimaging.org/
L2  - http://2020.biomedicalimaging.org/
N2  - The image-based simulations in biomedicine play an important role as the real image data are difficult to be fully and precisely annotated. An increasing capability of contemporary computers allows to model and simulate reasonably complicated structures and in the last years also the dynamic processes. In this paper, we introduce a complex 3D model that describes the structure and dynamics of the population of endothelial cells. The model is based on standard cellular Potts model. It describes the formation process of a complex tubular network of endothelial cells fully in 3D together with the simulation of the cell death called apoptosis. The generated network imitates the structure and behavior that can be observed in real phase-contrast microscopy. The generated image data may serve as a benchmark dataset for newly designed detection or tracking algorithms.
ER  -

SVOBODA, David and Tereza NEČASOVÁ. Image-based Simulations of Tubular Network Formation. Online. In \textit{17th IEEE International Symposium on Biomedical Imaging}. Neuveden: IEEE, 2020, p.~1608-1612. ISBN~978-1-5386-9330-8. Available from: https://dx.doi.org/10.1109/ISBI45749.2020.9098736.

Detailed Information on Publication Record