Grading Quality of Color Retinal Images to Assist Fundus Camera Operators

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F20%3APU138615" target="_blank" >RIV/00216305:26230/20:PU138615 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.fit.vut.cz/research/publication/12202/" target="_blank" >https://www.fit.vut.cz/research/publication/12202/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/CBMS49503.2020.00022" target="_blank" >10.1109/CBMS49503.2020.00022</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Grading Quality of Color Retinal Images to Assist Fundus Camera Operators

Popis výsledku v původním jazyce

Suitable image quality is a prerequisite to ensure accurate diagnosis or person recognition by color retinal images. Many factors during image acquisition, transferring and storing can result in poor quality retinal images. Poor quality images not only increase the possibility of wrong diagnosis, false acceptance, or incorrect identification but also increase diagnosis or recognition time. Therefore, retinal image quality assessment has become an important research topic. In general, only one color channel (most of the time either green or grayscale) is used to assess the quality of retinal images ignoring the quality of other channels. However, all image channels carry complementary information. In this paper, we propose a quality assessment approach for a colored retinal image to assist a fundus camera operator to judge the image quality. In our approach, we analyze the histogram of pixel intensity and uniformity of illumination, as well as check the presence of two main anatomical structures, optic disc, and central retinal blood vessels, in all color channels (i.e., red, green and blue) as well as in grayscale format.We show the effectiveness of our approach by grading 3090 color retinal images of five publicly available retinal databases.

Název v anglickém jazyce

Grading Quality of Color Retinal Images to Assist Fundus Camera Operators

Popis výsledku anglicky

Suitable image quality is a prerequisite to ensure accurate diagnosis or person recognition by color retinal images. Many factors during image acquisition, transferring and storing can result in poor quality retinal images. Poor quality images not only increase the possibility of wrong diagnosis, false acceptance, or incorrect identification but also increase diagnosis or recognition time. Therefore, retinal image quality assessment has become an important research topic. In general, only one color channel (most of the time either green or grayscale) is used to assess the quality of retinal images ignoring the quality of other channels. However, all image channels carry complementary information. In this paper, we propose a quality assessment approach for a colored retinal image to assist a fundus camera operator to judge the image quality. In our approach, we analyze the histogram of pixel intensity and uniformity of illumination, as well as check the presence of two main anatomical structures, optic disc, and central retinal blood vessels, in all color channels (i.e., red, green and blue) as well as in grayscale format.We show the effectiveness of our approach by grading 3090 color retinal images of five publicly available retinal databases.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/LQ1602" target="_blank" >LQ1602: IT4Innovations excellence in science</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

Proceedings of the IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS)

ISBN

978-1-7281-9429-5

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

77-82

Název nakladatele

IEEE Computer Society Press

Místo vydání

Rochester

Místo konání akce

Rochester

Datum konání akce

28. 7. 2020

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000786468800015