HASAL, Martin, Jana NOWAKOVÁ, Daniel HERNÁNDEZ-SOSA and Juraj TIMKOVIČ. Image Enhancement in Retinopathy of Prematurity. Online. In Advances in Intelligent Networking and Collaborative Systems. INCoS 2022. Lecture Notes in Networks and Systems. Springer, 2022, p. 422-431. ISBN 978-3-031-14626-8. Available from: https://dx.doi.org/10.1007/978-3-031-14627-5_43.
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Basic information
Original name Image Enhancement in Retinopathy of Prematurity
Authors HASAL, Martin, Jana NOWAKOVÁ, Daniel HERNÁNDEZ-SOSA and Juraj TIMKOVIČ.
Edition Advances in Intelligent Networking and Collaborative Systems. INCoS 2022. Lecture Notes in Networks and Systems. p. 422-431, 2022.
Publisher Springer
Other information
Original language English
Type of outcome Chapter(s) of a specialized book
Field of Study 30207 Ophthalmology
Country of publisher Switzerland
Confidentiality degree is not subject to a state or trade secret
Publication form electronic version available online
WWW URL
Organization unit Faculty of Medicine
ISBN 978-3-031-14626-8
Doi http://dx.doi.org/10.1007/978-3-031-14627-5_43
Tags topvydavatel
Tags International impact, Reviewed
Changed by Changed by: MUDr. Juraj Timkovič, Ph.D., učo 431399. Changed: 9/10/2022 20:51.
Abstract
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.
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