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

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F11%3A00051908" target="_blank" >RIV/00216224:14330/11:00051908 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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 nearreal-time performance in 2D.

Název v anglickém jazyce

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

Popis výsledku anglicky

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 nearreal-time performance in 2D.

Druh

O - Ostatní výsledky

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2011

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů