3-D Quantification of Filopodia in Motile Cancer Cells
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F19%3A00107178" target="_blank" >RIV/00216224:14330/19:00107178 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/TMI.2018.2873842" target="_blank" >https://doi.org/10.1109/TMI.2018.2873842</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TMI.2018.2873842" target="_blank" >10.1109/TMI.2018.2873842</a>
Alternative languages
Result language
angličtina
Original language name
3-D Quantification of Filopodia in Motile Cancer Cells
Original language description
We present a 3D bioimage analysis workflow to quantitatively analyze single, actin-stained cells with filopodial protrusions of diverse structural and temporal attributes, such as number, length, thickness, level of branching, and lifetime, in time-lapse confocal microscopy image data. Our workflow makes use of convolutional neural networks trained using real as well as synthetic image data, to segment the cell volumes with highly heterogeneous fluorescence intensity levels and to detect individual filopodial protrusions, followed by a constrained nearest-neighbor tracking algorithm to obtain valuable information about the spatio-temporal evolution of individual filopodia. We validated the workflow using real and synthetic 3-D time-lapse sequences of lung adenocarcinoma cells of three morphologically distinct filopodial phenotypes and show that it achieves reliable segmentation and tracking performance, providing a robust, reproducible and less time-consuming alternative to manual analysis of the 3D+t image data.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GJ16-03909Y" target="_blank" >GJ16-03909Y: Development of Reliable Methods for Automated Quantitative Characterization of Cell Motility in Fluorescence Microscopy</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE Transactions on Medical Imaging
ISSN
0278-0062
e-ISSN
1558-254X
Volume of the periodical
38
Issue of the periodical within the volume
3
Country of publishing house
US - UNITED STATES
Number of pages
11
Pages from-to
862-872
UT code for WoS article
000460662400019
EID of the result in the Scopus database
2-s2.0-85054522263