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Statements

Subject Item
n2:RIV%2F00216224%3A14330%2F11%3A00051908%21RIV12-MSM-14330___
rdf:type
skos:Concept n16:Vysledek
dcterms:description
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. 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.
dcterms:title
Fast Tracking Algorithm of GFP-Transfected Living Cells Based on the Chan-Vese Model Fast Tracking Algorithm of GFP-Transfected Living Cells Based on the Chan-Vese Model
skos:prefLabel
Fast Tracking Algorithm of GFP-Transfected Living Cells Based on the Chan-Vese Model Fast Tracking Algorithm of GFP-Transfected Living Cells Based on the Chan-Vese Model
skos:notation
RIV/00216224:14330/11:00051908!RIV12-MSM-14330___
n16:predkladatel
n17:orjk%3A14330
n3:aktivita
n7:S n7:P n7:Z
n3:aktivity
P(2B06052), P(LC535), S, Z(MSM0021622419)
n3:dodaniDat
n8:2012
n3:domaciTvurceVysledku
n5:9021094 n5:9465146
n3:druhVysledku
n6:O
n3:duvernostUdaju
n19:S
n3:entitaPredkladatele
n10:predkladatel
n3:idSjednocenehoVysledku
199374
n3:idVysledku
RIV/00216224:14330/11:00051908
n3:jazykVysledku
n13:eng
n3:klicovaSlova
object tracking; Chan-Vese model; level set framework; coherence-enhancing diffusion
n3:klicoveSlovo
n4:level%20set%20framework n4:coherence-enhancing%20diffusion n4:Chan-Vese%20model n4:object%20tracking
n3:kontrolniKodProRIV
[1BA609D14D07]
n3:obor
n14:IN
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
4
n3:projekt
n18:LC535 n18:2B06052
n3:rokUplatneniVysledku
n8:2011
n3:tvurceVysledku
Muñoz-Barrutia, Arrate Maška, Martin Matula, Pavel Ortiz-de-Solórzano, Carlos
n3:zamer
n9:MSM0021622419
n15:organizacniJednotka
14330