Color normalization for robust evaluation of microscopy images

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00023001%3A_____%2F15%3A00059744" target="_blank" >RIV/00023001:_____/15:00059744 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21230/15:00235502 RIV/60461373:22340/15:43899542

Výsledek na webu

<a href="http://dx.doi.org/10.1117/12.2188236" target="_blank" >http://dx.doi.org/10.1117/12.2188236</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1117/12.2188236" target="_blank" >10.1117/12.2188236</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Color normalization for robust evaluation of microscopy images

Popis výsledku v původním jazyce

This paper deals with color normalization of microscopy images of Langerhans islets in order to increase robustness of the islet segmentation to illumination changes. The main application is automatic quantitative evaluation of the islet parameters, useful for determining the feasibility of islet transplantation in diabetes. First, background illumination inhomogeneity is compensated and a preliminary foreground/background segmentation is performed. The color normalization itself is done in either l alpha beta or logarithmic RGB color spaces, by comparison with a reference image. The color-normalized images are segmented using color-based features and pixel-wise logistic regression, trained on manually labeled images. Finally, relevant statistics such as the total islet area are evaluated in order to determine the success likelihood of the transplantation. The robustness of the evaluation is increased dramatically by the color normalization, decreasing the image-wise failure rate from 17% to 0 % and the equal error rate from 30 % to 1 %.

Název v anglickém jazyce

Color normalization for robust evaluation of microscopy images

Popis výsledku anglicky

This paper deals with color normalization of microscopy images of Langerhans islets in order to increase robustness of the islet segmentation to illumination changes. The main application is automatic quantitative evaluation of the islet parameters, useful for determining the feasibility of islet transplantation in diabetes. First, background illumination inhomogeneity is compensated and a preliminary foreground/background segmentation is performed. The color normalization itself is done in either l alpha beta or logarithmic RGB color spaces, by comparison with a reference image. The color-normalized images are segmented using color-based features and pixel-wise logistic regression, trained on manually labeled images. Finally, relevant statistics such as the total islet area are evaluated in order to determine the success likelihood of the transplantation. The robustness of the evaluation is increased dramatically by the color normalization, decreasing the image-wise failure rate from 17% to 0 % and the equal error rate from 30 % to 1 %.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10306 - Optics (including laser optics and quantum optics)

Projekt

<a href="/cs/project/GA14-10440S" target="_blank" >GA14-10440S: Automatická analýza mikroskopických snímků Langerhansových ostrůvků</a><br>

Návaznosti

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

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název statě ve sborníku

Applications of digital image processing XXXVIII

ISBN

978-1-62841-765-4

ISSN

0277-786X

e-ISSN

1996-756X

Počet stran výsledku

6

Strana od-do

"95992F"

Název nakladatele

SPIE

Místo vydání

Bellingham

Místo konání akce

San Diego, US

Datum konání akce

10. 8. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000366385200071