Abstract：
:The detection and assessment of leakage in retinal fluorescein angiogram images is important for the management of a wide range of retinal diseases. We have developed a framework that can automatically detect three types of leakage (large focal, punctate focal, and vessel segment leakage) and validated it on images from patients with malarial retinopathy. This framework comprises three steps: vessel segmentation, saliency feature generation and leakage detection. We tested the effectiveness of this framework by applying it to images from 20 patients with large focal leak, 10 patients with punctate focal leak, and 5,846 vessel segments from 10 patients with vessel leakage. The sensitivity in detecting large focal, punctate focal and vessel segment leakage are 95%, 82% and 81%, respectively, when compared to manual annotation by expert human observers. Our framework has the potential to become a powerful new tool for studying malarial retinopathy, and other conditions involving retinal leakage.
journal_name
Sci Repjournal_title
Scientific reportsauthors
Zhao Y,MacCormick IJ,Parry DG,Leach S,Beare NA,Harding SP,Zheng Ydoi
10.1038/srep10425subject
Has Abstractpub_date
2015-06-01 00:00:00pages
10425issn
2045-2322pii
srep10425journal_volume
5pub_type
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