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DRNet: Segmentation and localization of optic disc and Fovea from diabetic retinopathy image

Author Affiliations
Khulna University of Engineering and Technology, University of Girona
Published InArtificial Intelligence in Medicine
Year2020
Citations97

Abstract

BACKGROUND AND OBJECTIVE In modern ophthalmology, automated Computer-aided Screening Tools (CSTs) are crucial non-intrusive diagnosis methods, where an accurate segmentation of Optic Disc (OD) and localization of OD and Fovea centers are substantial integral parts. However, designing such an automated tool remains challenging due to small dataset sizes, inconsistency in spatial, texture, and shape information of the OD and Fovea, and the presence of different artifacts. METHODS This article proposes an end-to-end encoder-decoder network, named DRNet, for the segmentation and localization of OD and Fovea centers. In our DRNet, we propose a skip connection, named residual skip connection, for compensating the spatial information lost due to pooling in the encoder. Unlike the earlier skip connection in the UNet, the proposed…
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