Optic Disc and Optic Cup Segmentation for Glaucoma Detection from Blur Retinal Images Using Improved Mask-RCNN

Tahira Nazir; Aun Irtaza; Valery Starovoitov

doi:10.1155/2021/6641980

journal article Open Access Jul 21, 2021

Optic Disc and Optic Cup Segmentation for Glaucoma Detection from Blur Retinal Images Using Improved Mask-RCNN

Tahira Nazir

Aun Irtaza

Valery Starovoitov

International Journal of Optics Vol. 2021 pp. 1-12 · Wiley

View at Publisher Save 10.1155/2021/6641980

Abstract

Glaucoma is a fatal eye disease that harms the optic disc (OD) and optic cup (OC) and results into blindness in progressed phases. Because of slow progress, the disease exhibits a small number of symptoms in the initial stages, therefore causing the disease identification to be a complicated task. So, a fully automatic framework is mandatory, which can support the screening process and increase the chances of disease detection in the early stages. In this paper, we deal with the localization and segmentation of the OD and OC for glaucoma detection from blur retinal images. We have presented a novel method that is Densenet-77-based Mask-RCNN to overcome the challenges of the glaucoma detection. Initially, we have performed the data augmentation step together with adding blurriness in samples to increase the diversity of data. Then, we have generated the annotations from ground-truth (GT) images. After that, the Densenet-77 framework is employed at the feature extraction level of Mask-RCNN to compute the deep key points. Finally, the calculated features are used to localize and segment the OD and OC by the custom Mask-RCNN model. For performance evaluation, we have used the ORIGA dataset that is publicly available. Furthermore, we have performed cross-dataset validation on the HRF database to show the robustness of the presented framework. The presented framework has achieved an average precision, recall, F-measure, and IOU as 0.965, 0.963, 0.97, and 0.972, respectively. The proposed method achieved remarkable performance in terms of both efficiency and effectiveness as compared to the latest techniques under the presence of blurring, noise, and light variations.

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Details

Published: Jul 21, 2021
Vol/Issue: 2021
Pages: 1-12
License: View

Authors

T

Tahira Nazir

Department of Computer Science, University of Engineering and Technology, Taxila 47050, Pakistan

A

Aun Irtaza

Department of Computer Science, University of Engineering and Technology, Taxila 47050, Pakistan

V

Valery Starovoitov

United Institute of Informatics Problems of the National Academy of Sciences of Belarus, Minsk 220012, Belarus

Cite This Article

Tahira Nazir, Aun Irtaza, Valery Starovoitov (2021). Optic Disc and Optic Cup Segmentation for Glaucoma Detection from Blur Retinal Images Using Improved Mask-RCNN. International Journal of Optics, 2021, 1-12. https://doi.org/10.1155/2021/6641980

Optic Disc and Optic Cup Segmentation for Glaucoma Detection from Blur Retinal Images Using Improved Mask-RCNN

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