Segmentation Method of Time-Lapse Microscopy Images with the Focus on Biocompatibility Assessment

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F16%3A00460642" target="_blank" >RIV/67985556:_____/16:00460642 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/60076658:12520/16:43890555 RIV/00216208:11320/16:10324380

Výsledek na webu

<a href="http://dx.doi.org/10.1017/S143192761600074X" target="_blank" >http://dx.doi.org/10.1017/S143192761600074X</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1017/S143192761600074X" target="_blank" >10.1017/S143192761600074X</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Segmentation Method of Time-Lapse Microscopy Images with the Focus on Biocompatibility Assessment

Popis výsledku v původním jazyce

Biocompatibility testing of new materials is often performed in vitro by measuring the growth rate of mammalian cancer cells in time-lapse images acquired by phase contrast microscopes. The growth rate is measured by tracking cell coverage, which requires an accurate automatic segmentation method. However, cancer cells have irregular shapes that change over time, the mottled background pattern is partially visible through the cells and the images contain artifacts such as halos. We developed a novel algorithm for cell segmentation that copes with the mentioned challenges. It is based on temporal differences of consecutive images and a combination of thresholding, blurring and morphological operations. We tested the algorithm on images of four cell types acquired by two different microscopes, evaluated the precision of segmentation against manual segmentation performed by a human operator and finally provided comparison with other freely available methods.

Název v anglickém jazyce

Segmentation Method of Time-Lapse Microscopy Images with the Focus on Biocompatibility Assessment

Popis výsledku anglicky

Biocompatibility testing of new materials is often performed in vitro by measuring the growth rate of mammalian cancer cells in time-lapse images acquired by phase contrast microscopes. The growth rate is measured by tracking cell coverage, which requires an accurate automatic segmentation method. However, cancer cells have irregular shapes that change over time, the mottled background pattern is partially visible through the cells and the images contain artifacts such as halos. We developed a novel algorithm for cell segmentation that copes with the mentioned challenges. It is based on temporal differences of consecutive images and a combination of thresholding, blurring and morphological operations. We tested the algorithm on images of four cell types acquired by two different microscopes, evaluated the precision of segmentation against manual segmentation performed by a human operator and finally provided comparison with other freely available methods.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

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

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název periodika

Microscopy and Microanalysis

ISSN

1431-9276

e-ISSN

—

Svazek periodika

22

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

10

Strana od-do

497-506

Kód UT WoS článku

000384332600003

EID výsledku v databázi Scopus

2-s2.0-84964751084