Screening of Glaucoma disease from retinal vessel images using semantic segmentation

A timely diagnosis of Glaucoma has crucial importance in preventing blindness. As this disease exists in the immediate vicinity of the optical disk (OD), its precise localization and segmentation are critical in its accurate diagnosis. OD consists of two parts, namely: neuroretinal and optic cup (OC...

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Bibliographic Details
Published inComputers & electrical engineering Vol. 91; p. 107036
Main Authors Imtiaz, Rakhshanda, Khan, Tariq M., Naqvi, Syed Saud, Arsalan, Muhammad, Nawaz, Syed Junaid
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier Ltd 01.05.2021
Elsevier BV
Subjects
Blindness
Deep neural networks
Diagnosis
Glaucoma
Image segmentation
Medical imaging
Optic cup
Optic disk
Post-production processing
Semantic segmentation
Semantics
Glaucoma
Image segmentation
Optic disk
Deep neural networks
Optic cup
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Summary:A timely diagnosis of Glaucoma has crucial importance in preventing blindness. As this disease exists in the immediate vicinity of the optical disk (OD), its precise localization and segmentation are critical in its accurate diagnosis. OD consists of two parts, namely: neuroretinal and optic cup (OC). In the proposed work, the problem of OD and OC segmentation is modeled as a semantic pixel-wise labeling problem, thus bridging the gap between medical image segmentation and semantic segmentation. The proposed method eliminates the need for pre- and post-processing steps. The proposed method is evaluated for the segmentation of OD and OC on Drishti and Rim-one datasets. The offered low computational and resource requirements along with the observed state-of-the-art accuracy of the proposed method support its implementation in the real-time automatic screening of the Glaucoma disease.
ISSN:0045-7906
1879-0755
DOI:10.1016/j.compeleceng.2021.107036