Image enhancement in retinopathy of prematurity
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00843989%3A_____%2F22%3AE0110141" target="_blank" >RIV/00843989:_____/22:E0110141 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-031-14627-5_43" target="_blank" >http://dx.doi.org/10.1007/978-3-031-14627-5_43</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-14627-5_43" target="_blank" >10.1007/978-3-031-14627-5_43</a>
Alternative languages
Result language
angličtina
Original language name
Image enhancement in retinopathy of prematurity
Original language description
Retinopathy of prematurity (ROP) is an ocular disease caused by abnormal retinal blood vessel growth of premature infants. All premature infants who fall within a screening protocol (birth weight less than 1500 g and gestational age below 32 weeks) are diagnosed by an ophthalmological specialist for ROP. Early recognition of ROP and other diseases of premature infants leads to better treatment. The examination is provided by special cameras, which take a snapshot of the posterior segment of the eye (fundus). The taken retinal images are not always perfect. The images can be dark, with low contrast, or difficult to distinguish necessary patterns for diagnosis. This article examines the image enhancement methods of the fundus, such as transformation to green or grayscale channel, adaptive histogram equalisation methods, Gaussian smoothing, and contrast enhancement. These methods improve the image quality in computer-aided diagnosis of the fundus of prematurely born infants. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
30207 - Ophthalmology
Result continuities
Project
—
Continuities
V - Vyzkumna aktivita podporovana z jinych verejnych zdroju
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Advances in intelligent networking and collaborative systems, INCOS-2022
ISBN
978-3-031-14627-5
ISSN
2367-3370
e-ISSN
2367-3389
Number of pages
10
Pages from-to
422-431
Publisher name
—
Place of publication
Cham : Springer, 2022
Event location
Kwansei Gakuin Univ, Nishinomiya, JAPAN
Event date
Sep 7, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000870692600043