A robust algorithm for optic disc segmentation and fovea detection in retinal fundus images
Abstract: Accurate optic disc (OD) segmentation and fovea detection in retinal fundus images are crucial for diagnosis in ophthalmology. We propose a robust and broadly applicable algorithm for automated, robust, reliable and consistent fovea detection based on OD segmentation. The OD segmentation is performed with morphological operations and Fuzzy C Means Clustering combined with iterative thresholding on a foreground segmentation. The fovea detection is based on a vessel segmentation via morphological operations and uses the resulting OD segmentation to determine multiple regions of interest. The fovea is determined from the largest, vessel-free candidate region. We have tested the novel method on a total of 190 images from three publicly available databases DRIONS, Drive and HRF. Compared to results of two human experts for DRIONS database, our OD segmentation yielded a dice coefficient of 0.83. Note that missing ground truth and expert variability is an issue. The new scheme achieved an overall success rate of 99.44% for OD detection and an overall success rate of 96.25% for fovea detection, which is superior to state-of-the-art approaches.
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource
- Language
-
Englisch
- Bibliographic citation
-
A robust algorithm for optic disc segmentation and fovea detection in retinal fundus images ; volume:3 ; number:2 ; year:2017 ; pages:533-537 ; extent:5
Current directions in biomedical engineering ; 3, Heft 2 (2017), 533-537 (gesamt 5)
- Creator
-
Rust, Caterina
Häger, Stephanie
Traulsen, Nadine
Modersitzki, Jan
- DOI
-
10.1515/cdbme-2017-0113
- URN
-
urn:nbn:de:101:1-2023030713123917666235
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
14.08.2025, 10:55 AM CEST
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Rust, Caterina
- Häger, Stephanie
- Traulsen, Nadine
- Modersitzki, Jan
Other Objects (12)
Research on segmentation model of optic disc and optic cup in fundus
Optic cup segmentation of stereo retinal fundus images using virtual reality
Automated segmentation and quantitative analysis of optic disc and fovea in fundus images
Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning
Multiresolution cascaded attention U-Net for localization and segmentation of optic disc and fovea in fundus images
Development of a deep learning model to distinguish the cause of optic disc atrophy using retinal fundus photography
Deep learning on fundus images detects glaucoma beyond the optic disc
Correction to: Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning
Optic disc localization in retinal images using histogram matching
Discriminating Healthy Optic Discs and Visible Optic Disc Drusen on Fundus Autofluorescence and Color Fundus Photography Using Deep Learning—A Pilot Study
Author Correction: Deep learning on fundus images detects glaucoma beyond the optic disc
Association between retinal microvasculature and optic disc alterations in high myopia
Research on segmentation model of optic disc and optic cup in fundus
Optic cup segmentation of stereo retinal fundus images using virtual reality
Automated segmentation and quantitative analysis of optic disc and fovea in fundus images
Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning
Multiresolution cascaded attention U-Net for localization and segmentation of optic disc and fovea in fundus images
Development of a deep learning model to distinguish the cause of optic disc atrophy using retinal fundus photography
Deep learning on fundus images detects glaucoma beyond the optic disc
Correction to: Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning
Optic disc localization in retinal images using histogram matching
Discriminating Healthy Optic Discs and Visible Optic Disc Drusen on Fundus Autofluorescence and Color Fundus Photography Using Deep Learning—A Pilot Study
Author Correction: Deep learning on fundus images detects glaucoma beyond the optic disc
Association between retinal microvasculature and optic disc alterations in high myopia
Research on segmentation model of optic disc and optic cup in fundus
Optic cup segmentation of stereo retinal fundus images using virtual reality
Automated segmentation and quantitative analysis of optic disc and fovea in fundus images
Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning
Multiresolution cascaded attention U-Net for localization and segmentation of optic disc and fovea in fundus images
Development of a deep learning model to distinguish the cause of optic disc atrophy using retinal fundus photography
Deep learning on fundus images detects glaucoma beyond the optic disc
Correction to: Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning
Optic disc localization in retinal images using histogram matching
Discriminating Healthy Optic Discs and Visible Optic Disc Drusen on Fundus Autofluorescence and Color Fundus Photography Using Deep Learning—A Pilot Study
Author Correction: Deep learning on fundus images detects glaucoma beyond the optic disc