Automated Fovea Detection in Spectral Domain Optical Coherence Tomography Scans of Exudative Macular Disease
Joint Authors
Schmidt-Erfurth, Ursula
Wu, Jing
Waldstein, Sebastian M.
Montuoro, Alessio
Gerendas, Bianca S.
Langs, Georg
Source
International Journal of Biomedical Imaging
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-08-31
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
In macular spectral domain optical coherence tomography (SD-OCT) volumes, detection of the foveal center is required for accurate and reproducible follow-up studies, structure function correlation, and measurement grid positioning.
However, disease can cause severe obscuring or deformation of the fovea, thus presenting a major challenge in automated detection.
We propose a fully automated fovea detection algorithm to extract the fovea position in SD-OCT volumes of eyes with exudative maculopathy.
The fovea is classified into 3 main appearances to both specify the detection algorithm used and reduce computational complexity.
Based on foveal type classification, the fovea position is computed based on retinal nerve fiber layer thickness.
Mean absolute distance between system and clinical expert annotated fovea positions from a dataset comprised of 240 SD-OCT volumes was 162.3 µm in cystoid macular edema and 262 µm in nAMD.
The presented method has cross-vendor functionality, while demonstrating accurate and reliable performance close to typical expert interobserver agreement.
The automatically detected fovea positions may be used as landmarks for intra- and cross-patient registration and to create a joint reference frame for extraction of spatiotemporal features in “big data.” Furthermore, reliable analyses of retinal thickness, as well as retinal structure function correlation, may be facilitated.
American Psychological Association (APA)
Wu, Jing& Waldstein, Sebastian M.& Montuoro, Alessio& Gerendas, Bianca S.& Langs, Georg& Schmidt-Erfurth, Ursula. 2016. Automated Fovea Detection in Spectral Domain Optical Coherence Tomography Scans of Exudative Macular Disease. International Journal of Biomedical Imaging،Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1105428
Modern Language Association (MLA)
Wu, Jing…[et al.]. Automated Fovea Detection in Spectral Domain Optical Coherence Tomography Scans of Exudative Macular Disease. International Journal of Biomedical Imaging No. 2016 (2016), pp.1-9.
https://search.emarefa.net/detail/BIM-1105428
American Medical Association (AMA)
Wu, Jing& Waldstein, Sebastian M.& Montuoro, Alessio& Gerendas, Bianca S.& Langs, Georg& Schmidt-Erfurth, Ursula. Automated Fovea Detection in Spectral Domain Optical Coherence Tomography Scans of Exudative Macular Disease. International Journal of Biomedical Imaging. 2016. Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1105428
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1105428