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- W4387396855 abstract "Abstract Purpose The optic disc and the macular are two major anatomical structures in the human eye. Optic discs are associated with the optic nerve. Macular mainly involves degeneration and impaired function of the macular region. Reliable optic disc and macular segmentation are necessary for the automated screening of retinal diseases. Methods A swept‐source OCTA system was designed to capture OCTA images of human eyes. To address these segmentation tasks, firstly, we constructed a new O ptic D isc and M acula in fundus I mage with Optical Coherence Tomography Angiography (OCTA) dataset ( ODMI ). Secondly, we proposed a C oarse and F ine A ttention‐Based Net work ( CFANet ). Results The five metrics of our methods on ODMI are 98.91%, 98.47%, 89.77%, 98.49%, and 89.77%, respectively. Conclusions Experimental results show that our CFANet has achieved good performance on segmentation for the optic disc and macula in OCTA. This article is protected by copyright. All rights reserved." @default.
- W4387396855 created "2023-10-07" @default.
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- W4387396855 date "2023-10-06" @default.
- W4387396855 modified "2023-10-18" @default.
- W4387396855 title "Deep‐learning segmentation method for optical coherence tomography angiography in ophthalmology" @default.
- W4387396855 doi "https://doi.org/10.1002/jbio.202300321" @default.
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