Segmentation of Touching Cell Nuclei using a Two-Stage Graph Cut Model

Kód výsledku v IS VaVaI

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Nalezeny alternativní kódy

RIV/00216224:14330/09:00067107

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Segmentation of Touching Cell Nuclei using a Two-Stage Graph Cut Model

Popis výsledku v původním jazyce

Methods based on combinatorial graph cut algorithms received a lot of attention in the recent years for their robustness as well as reasonable computational demands. These methods are built upon an underlying maximum a posteriori estimation of Markov random fields and are suitable to solve accurately many different problems in image analysis, including image segmentation. In this paper we propose a two-stage graph cut based model for segmentation of touching cell nuclei in fluorescence microscopy images. In the first stage voxels with very high probability of being foreground or background are found and separated by a boundary with a minimal geodesic length. In the second stage the obtained clusters are split into isolated cells by combining image gradient information and incorporated a priori knowledge about the shape of the nuclei. Moreover, these two qualities can be easily balanced using a single user parameter. Preliminary tests on real data show promising results of the method.

Název v anglickém jazyce

Segmentation of Touching Cell Nuclei using a Two-Stage Graph Cut Model

Popis výsledku anglicky

Methods based on combinatorial graph cut algorithms received a lot of attention in the recent years for their robustness as well as reasonable computational demands. These methods are built upon an underlying maximum a posteriori estimation of Markov random fields and are suitable to solve accurately many different problems in image analysis, including image segmentation. In this paper we propose a two-stage graph cut based model for segmentation of touching cell nuclei in fluorescence microscopy images. In the first stage voxels with very high probability of being foreground or background are found and separated by a boundary with a minimal geodesic length. In the second stage the obtained clusters are split into isolated cells by combining image gradient information and incorporated a priori knowledge about the shape of the nuclei. Moreover, these two qualities can be easily balanced using a single user parameter. Preliminary tests on real data show promising results of the method.

Druh

D - Stať ve sborníku

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)

Rok uplatnění

2009

Kód důvěrnosti údajů

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

Název statě ve sborníku

16th Scandinavian Conference on Image Analysis

ISBN

978-3-642-02229-6

ISSN

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e-ISSN

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Počet stran výsledku

10

Strana od-do

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Název nakladatele

Springer-Verlag

Místo vydání

Berlin, Heidelberg

Místo konání akce

Oslo

Datum konání akce

15. 6. 2009

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000268661000042