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Visualising ganglion cell layer based on image entropy optimisation for adaptive contrast enhancement

Authors
Han, J-HCha, J.
Issue Date
9-1월-2020
Publisher
INST ENGINEERING TECHNOLOGY-IET
Citation
ELECTRONICS LETTERS, v.56, no.1, pp.25 - +
Indexed
SCIE
SCOPUS
Journal Title
ELECTRONICS LETTERS
Volume
56
Number
1
Start Page
25
End Page
+
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/58324
DOI
10.1049/el.2019.3006
ISSN
0013-5194
Abstract
Optical coherence tomography cannot easily be used for visual identification of the ganglion cell layer (GCL) for diagnosing retinal diseases owing to the extremely low image contrast between adjacent layers. To solve this problem. the authors used a limit-clipping optimisation method along with the image entropy to enhance the image contrast of targeted layers. As a result, the GCL was successfully extracted using an intelligent tracking system without impacting the segmentation of other retinal layers and image morphology. The segmentation results were evaluated through comparisons with manual segmentation results provided by clinical experts. The results of this study should help realise simple and efficient discrimination of important retinal layers for the early diagnosis of glaucoma.
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