Publication Details

Grading Quality of Color Retinal Images to Assist Fundus Camera Operators

BISWAS, S.; ROHDIN, J.; KAVETSKYI, A.; DRAHANSKÝ, M. Grading Quality of Color Retinal Images to Assist Fundus Camera Operators. In Proceedings of the IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS). Rochester: IEEE Computer Society Press, 2020. p. 77-82. ISBN: 978-1-7281-9429-5.
Czech title
Hodnocení kvality barevných obrazů sítnice na pomoc operátorům fundus kamer
Type
conference paper
Language
English
Authors
Biswas Sangeeta, Ph.D. (UITS)
Rohdin Johan Andréas, M.Sc., Ph.D. (DCGM)
Kavetskyi Andrii (DITS)
Drahanský Martin, prof. Ing., Ph.D.
Keywords

color retinal image, quality assessment, convolutional neural network

Abstract

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.

Published
2020
Pages
77–82
Proceedings
Proceedings of the IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS)
Conference
IEEE 33rd International Symposium on Computer-Based Medical Systems, Rochester, US
ISBN
978-1-7281-9429-5
Publisher
IEEE Computer Society Press
Place
Rochester
DOI
10.1109/CBMS49503.2020.00022
UT WoS
000786468800015
EID Scopus
2-s2.0-85091158873
BibTeX 
@inproceedings{BUT168124,
  author="Sangeeta {Biswas} and Johan Andréas {Rohdin} and Andrii {Kavetskyi} and Martin {Drahanský}",
  title="Grading Quality of Color Retinal Images to Assist Fundus Camera Operators",
  booktitle="Proceedings of the IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS)",
  year="2020",
  pages="77--82",
  publisher="IEEE Computer Society Press",
  address="Rochester",
  doi="10.1109/CBMS49503.2020.00022",
  isbn="978-1-7281-9429-5",
  url="https://www.fit.vut.cz/research/publication/12202/"
}
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