Automatic Quantification of Filopodia-Based Cell Migration

D 2013

Automatic Quantification of Filopodia-Based Cell Migration

MAŠKA, Martin; Xabier MORALES; Arrate MUÑOZ-BARRUTIA; Ana ROUZAUT; Carlos ORTIZ-DE-SOLÓRZANO et al.

Základní údaje

Originální název

Automatic Quantification of Filopodia-Based Cell Migration

Autoři

MAŠKA, Martin ; Xabier MORALES; Arrate MUÑOZ-BARRUTIA; Ana ROUZAUT a Carlos ORTIZ-DE-SOLÓRZANO

Vydání

San Francisco, 10th IEEE International Symposium on Biomedical Imaging, od s. 668-671, 4 s. 2013

Nakladatel

IEEE

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

elektronická verze "online"

Odkazy

URL

Označené pro přenos do RIV

Ano

Kód RIV

RIV/00216224:14330/13:00068040

Organizační jednotka

Fakulta informatiky

ISBN

978-1-4673-6454-6

ISSN

DOI

https://doi.org/10.1109/ISBI.2013.6556563

UT WoS

000326900100167

Klíčová slova anglicky

Filopodium segmentation;fluorescence microscopy;steerable filtering;geodesic distance

Štítky

cbia-web, firank_B

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 24. 4. 2014 18:07, RNDr. Pavel Šmerk, Ph.D.

Anotace

V originále

We present a fully automatic approach to quantitatively analyze filopodia-based migration of fluorescent cells in 3D time-lapse series. The proposed method involves three steps. First, each frame of the time-lapse series is preprocessed using a steerable filter and binarized to obtain a coarse segmentation of the cell shape. Second, a sequence of morphological filters is applied on the coarse binary mask to separate the cell body from individual filopodia. Finally, their length is estimated using a geodesic distance transform. The proposed approach is validated on 3D time-lapse series of lung adenocarcinoma cells. We show that the number of filopodia and their average length can be used as a descriptor to discriminate between different phenotypes of migrating cells.

Návaznosti

EE2.3.30.0009, projekt VaV

Název: Zaměstnáním čerstvých absolventů doktorského studia k vědecké excelenci

Citovat

MAŠKA, Martin; Xabier MORALES; Arrate MUÑOZ-BARRUTIA; Ana ROUZAUT a Carlos ORTIZ-DE-SOLÓRZANO. Automatic Quantification of Filopodia-Based Cell Migration. Online. In 10th IEEE International Symposium on Biomedical Imaging. San Francisco: IEEE, 2013, s. 668-671. ISBN 978-1-4673-6454-6. Dostupné z: https://doi.org/10.1109/ISBI.2013.6556563.

@inproceedings{1094756,
   author = {Maška, Martin and Morales, Xabier and MuñozandBarrutia, Arrate and Rouzaut, Ana and OrtizanddeandSolórzano, Carlos},
   address = {San Francisco},
   booktitle = {10th IEEE International Symposium on Biomedical Imaging},
   doi = {https://doi.org/10.1109/ISBI.2013.6556563},
   keywords = {Filopodium segmentation;fluorescence microscopy;steerable filtering;geodesic distance},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {San Francisco},
   isbn = {978-1-4673-6454-6},
   pages = {668-671},
   publisher = {IEEE},
   title = {Automatic Quantification of Filopodia-Based Cell Migration},
   url = {http://dx.doi.org/10.1109/ISBI.2013.6556563},
   year = {2013}
}

TY  - CONF
ID  - 1094756
AU  - Maška, Martin - Morales, Xabier - Muñoz-Barrutia, Arrate - Rouzaut, Ana - Ortiz-de-Solórzano, Carlos
PY  - 2013
TI  - Automatic Quantification of Filopodia-Based Cell Migration
PB  - IEEE
CY  - San Francisco
SN  - 9781467364546
KW  - Filopodium segmentation;fluorescence microscopy;steerable filtering;geodesic distance
UR  - http://dx.doi.org/10.1109/ISBI.2013.6556563
N2  - We present a fully automatic approach to quantitatively analyze filopodia-based migration of fluorescent cells in 3D time-lapse series. The proposed method involves three steps. First, each frame of the time-lapse series is preprocessed using a steerable filter and binarized to obtain a coarse segmentation of the cell shape. Second, a sequence of morphological filters is applied on the coarse binary mask to separate the cell body from individual filopodia. Finally, their length is estimated using a geodesic distance transform. The proposed approach is validated on 3D time-lapse series of lung adenocarcinoma cells. We show that the number of filopodia and their average length can be used as a descriptor to discriminate between different phenotypes of migrating cells.
ER  -

MAŠKA, Martin; Xabier MORALES; Arrate MUÑOZ-BARRUTIA; Ana ROUZAUT a Carlos ORTIZ-DE-SOLÓRZANO. Automatic Quantification of Filopodia-Based Cell Migration. Online. In \textit{10th IEEE International Symposium on Biomedical Imaging}. San Francisco: IEEE, 2013, s.~668-671. ISBN~978-1-4673-6454-6. Dostupné z: https://doi.org/10.1109/ISBI.2013.6556563.

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