a 2011

Fast Tracking Algorithm of GFP-Transfected Living Cells Based on the Chan-Vese Model

MAŠKA, Martin, Pavel MATULA, Arrate MUÑOZ-BARRUTIA and Carlos ORTIZ-DE-SOLÓRZANO

Basic information

Original name

Fast Tracking Algorithm of GFP-Transfected Living Cells Based on the Chan-Vese Model

Name in Czech

Rychlý algoritmus na sledování pohybu živých buněk transfekovaných pomocí GFP založený na Chan-Vese modelu

Authors

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

Edition

2011

Other information

Language

English

Type of outcome

Konferenční abstrakt

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Germany

Confidentiality degree

není předmětem státního či obchodního tajemství

RIV identification code

RIV/00216224:14330/11:00051908

Organization unit

Faculty of Informatics

Keywords in English

object tracking; Chan-Vese model; level set framework; coherence-enhancing diffusion

Tags

Tags

International impact, Reviewed
Změněno: 13/4/2011 10:32, doc. RNDr. Martin Maška, Ph.D.

Abstract

ORIG CZ

V originále

We present a general, robust, and fast approach for tracking GFP-transfected living cells in time-lapse series acquired using a confocal fluorescence microscope. The proposed tracking scheme involves two steps. First, the coherence-enhancing diffusion filtering is applied on each frame in order to reduce the noise and enhance flow-like structures. Second, enhanced cell boundaries are detected through a minimization of the Chan-Vese model that divides an image domain into two possibly disconnected regions of minimal variance. To speed up the second step, final contours from the previous frame are taken as seeds in the next one. The minimization of the Chan-Vese model is implemented using a fast level set-like algorithm (Maška et al. 2010) achieving near real-time performance in 2D. Furthermore, this algorithm has been integrated with a topology-preserving constraint based on the simple point concept from digital geometry in order to preserve known topology from the first frame throughout the entire time-lapse series. Such constraint provides a simple and inherent mechanism for keeping the boundaries of two cells separated even if the cells get touched in subsequent frames. The potential and preliminary results of the proposed tracking algorithm are demonstrated on 2D as well as 3D time-lapse series. The image data used in our experiments was acquired using a Zeiss Cell Observer Spinning Disk confocal microscope equipped with a 20x Plan Apo (0.85 NA) objective lens. The execution time of the proposed tracking algorithm is about 0.55 seconds per a 2D frame of the size 512x512 pixels and about 30 seconds per a 3D frame of the size 512x512x42 voxels.

In Czech

Příspěvek pojednává o rychlém algoritmu na sledování pohybu živých buněk

Links

LC535, research and development project
Name: Dynamika a organizace chromosomů během buněčného cyklu v normě a patologii
Investor: Ministry of Education, Youth and Sports of the CR, Dynamika a organizace chromosomů během buněčného cyklu v normě a patologii
MSM0021622419, plan (intention)
Name: Vysoce paralelní a distribuované výpočetní systémy
Investor: Ministry of Education, Youth and Sports of the CR, Highly Parallel and Distributed Computing Systems
MUNI/A/0914/2009, interní kód MU
Name: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace (Acronym: SV-FI MAV)
Investor: Masaryk University, Category A
2B06052, research and development project
Name: Vytipování markerů, screening a časná diagnostika nádorových onemocnění pomocí vysoce automatizovaného zpracování multidimenzionálních biomedicínských obrazů (Acronym: Biomarker)
Investor: Ministry of Education, Youth and Sports of the CR, Determination of markers, screening and early diagnostics of cancer diseases using highly automated processing of multidimensional biomedical images