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.

Basic information

Original name

Automatic Quantification of Filopodia-Based Cell Migration

Authors

MAŠKA, Martin (203 Czech Republic, guarantor, belonging to the institution), Xabier MORALES (724 Spain), Arrate MUÑOZ-BARRUTIA (724 Spain), Ana ROUZAUT (724 Spain) and Carlos ORTIZ-DE-SOLÓRZANO (724 Spain)

Edition

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

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/00216224:14330/13:00068040

Organization unit

Faculty of Informatics

ISBN

978-1-4673-6454-6

ISSN

DOI

http://dx.doi.org/10.1109/ISBI.2013.6556563

UT WoS

000326900100167

Keywords in English

Filopodium segmentation;fluorescence microscopy;steerable filtering;geodesic distance

Abstract

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.

Links

EE2.3.30.0009, research and development project

Name: Zaměstnáním čerstvých absolventů doktorského studia k vědecké excelenci

Citovat

MAŠKA, Martin, Xabier MORALES, Arrate MUÑOZ-BARRUTIA, Ana ROUZAUT and Carlos ORTIZ-DE-SOLÓRZANO. Automatic Quantification of Filopodia-Based Cell Migration. Online. In 10th IEEE International Symposium on Biomedical Imaging. San Francisco: IEEE, 2013, p. 668-671. ISBN 978-1-4673-6454-6. Available from: https://dx.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 = {http://dx.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  - JOUR
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 and 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, p.~668-671. ISBN~978-1-4673-6454-6. Available from: https://dx.doi.org/10.1109/ISBI.2013.6556563.

Detailed Information on Publication Record