TRAgen: A Tool for Generation of Synthetic Time-Lapse Image Sequences of Living Cells
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F15%3A00080843" target="_blank" >RIV/00216224:14330/15:00080843 - isvavai.cz</a>
Výsledek na webu
<a href="http://dx.doi.org/10.1007/978-3-319-23231-7_56" target="_blank" >http://dx.doi.org/10.1007/978-3-319-23231-7_56</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-23231-7_56" target="_blank" >10.1007/978-3-319-23231-7_56</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
TRAgen: A Tool for Generation of Synthetic Time-Lapse Image Sequences of Living Cells
Popis výsledku v původním jazyce
In biomedical image processing, correct tracking of individual cells is important task for the study of dynamic cellular processes. It is, however, often difficult to decide whether obtained tracking results are correct or not. This is mainly due to complexity of the data that can show hundreds of cells, due to improper data sampling either in time or in space, or when the time-lapse sequence consists of blurred noisy images. This prohibits manual extraction of reliable ground truth (GT) data as well. Nonetheless, if reliable testing data with GT were available, one could compare the results of the examined tracking algorithm with the GT and assess its performance quantitatively. In this paper, we introduce a novel versatile tool capable of generating2D image sequences showing simulated living cell populations with GT for evaluation of biomedical tracking. The simulated events include namely cell motion, cell division, and cell clustering up to tissue-level density.
Název v anglickém jazyce
TRAgen: A Tool for Generation of Synthetic Time-Lapse Image Sequences of Living Cells
Popis výsledku anglicky
In biomedical image processing, correct tracking of individual cells is important task for the study of dynamic cellular processes. It is, however, often difficult to decide whether obtained tracking results are correct or not. This is mainly due to complexity of the data that can show hundreds of cells, due to improper data sampling either in time or in space, or when the time-lapse sequence consists of blurred noisy images. This prohibits manual extraction of reliable ground truth (GT) data as well. Nonetheless, if reliable testing data with GT were available, one could compare the results of the examined tracking algorithm with the GT and assess its performance quantitatively. In this paper, we introduce a novel versatile tool capable of generating2D image sequences showing simulated living cell populations with GT for evaluation of biomedical tracking. The simulated events include namely cell motion, cell division, and cell clustering up to tissue-level density.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
IN - Informatika
OECD FORD obor
—
Návaznosti výsledku
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)<br>S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2015
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
Proceedings of 18th International Conference on Image Analysis and Processing
ISBN
9783319232300
ISSN
0302-9743
e-ISSN
—
Počet stran výsledku
12
Strana od-do
623-634
Název nakladatele
Springer International Publishing
Místo vydání
Heidelberg, Německo
Místo konání akce
Janov
Datum konání akce
9. 9. 2015
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
000364991200056