Improving foveal avascular zone segmentation in fluorescein angiograms by leveraging manual vessel labels from public color fundus pictures

Improving foveal avascular zone segmentation in fluorescein angiograms by leveraging manual vessel labels from public color fundus pictures

In clinical routine, ophthalmologists frequently analyze the shape and size of the foveal avascular zone (FAZ) to detect and monitor retinal diseases. In order to extract those parameters, the contours of the FAZ need to be segmented, which is normally achieved by analyzing the retinal vasculature (...

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Bibliographic Details
Main Authors: Gerendas, B.S (Author), Goldbach, F. (Author), Hofer, D. (Author), Orlando, J.I (Author), Schmidt-Erfurth, U. (Author), Seeböck, P. (Author)
Format: Article
Language:English
Published: Optica Publishing Group (formerly OSA) 2022
Subjects:
Air navigation
Article
Clinical routine
clinical trial (topic)
Computer aided instruction
Computer-aided
'current
deep learning
Deep learning
eye fundus
fluorescein
foveal avascular zone
Foveal avascular zones
human
image segmentation
Image segmentation
Large dataset
Low qualities
multicenter study (topic)
ophthalmologist
Ophthalmology
optical coherence tomography
retina blood vessel
retina fluorescein angiography
retina neovascularization
Retinal disease
retinal nerve fiber layer thickness
Retinal vasculature
Segmentation methods
Shape and size
workflow
Work-flows
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