Cell Segmentation in Quantitative Phase Images with Improved Iterative Thresholding Method

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F20%3APU137881" target="_blank" >RIV/00216305:26220/20:PU137881 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007/978-3-030-64610-3_27" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-64610-3_27</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-64610-3_27" target="_blank" >10.1007/978-3-030-64610-3_27</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Cell Segmentation in Quantitative Phase Images with Improved Iterative Thresholding Method

Popis výsledku v původním jazyce

Quantitative Phase Imaging (QPI) is a label-free microscopic technique, which provides images with high contrast, moreover, it provides quantitative cell mass measurements for each pixel. Segmentation of particular cells is an important step in the analysis of QPI image data. This paper presents a method for automatic cell segmentation in QPI images. The proposed method improves iterative thresholding, which is a very promising method, however, it is not able to segment densely clustered cells. Our improved iterative thresholding includes two additional steps -- Laplacian of Gaussian image enhancement and distance transform-based splitting. The method was compared with original iterative thresholding and another method on two cell lines, where the proposed method successfully deals with a densely clustered type of cells and achieves significantly better results on both datasets

Název v anglickém jazyce

Cell Segmentation in Quantitative Phase Images with Improved Iterative Thresholding Method

Popis výsledku anglicky

Quantitative Phase Imaging (QPI) is a label-free microscopic technique, which provides images with high contrast, moreover, it provides quantitative cell mass measurements for each pixel. Segmentation of particular cells is an important step in the analysis of QPI image data. This paper presents a method for automatic cell segmentation in QPI images. The proposed method improves iterative thresholding, which is a very promising method, however, it is not able to segment densely clustered cells. Our improved iterative thresholding includes two additional steps -- Laplacian of Gaussian image enhancement and distance transform-based splitting. The method was compared with original iterative thresholding and another method on two cell lines, where the proposed method successfully deals with a densely clustered type of cells and achieves significantly better results on both datasets

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20601 - Medical engineering

Projekt

<a href="/cs/project/GA18-24089S" target="_blank" >GA18-24089S: Kvantitativní fázová mikroskopie pro 3D kvalitativní charakterizaci nádorových buněk</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2020

Kód důvěrnosti údajů

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

Název statě ve sborníku

EMBEC 2020, IFMBE Proceedings vol. 80

ISBN

978-3-030-64609-7

ISSN

1680-0737

e-ISSN

—

Počet stran výsledku

7

Strana od-do

233-239

Název nakladatele

Springer Nature Switzerland AG 2021

Místo vydání

Switzerland

Místo konání akce

Portorož

Datum konání akce

29. 11. 2020

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

—