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CITATION.cff
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# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 1.2.0
title: eyeseg
message: >-
If you use this software, please cite it using the
metadata from this file.
type: software
authors:
- given-names: Olivier
family-names: Morelle
email: [email protected]
affiliation: >-
University of Bonn - Bonn-Aachen International Center
for Information Technology (b-it) / University
Hospital Bonn - Department of Ophthalmology
orcid: 'https://orcid.org/0000-0001-6404-2726'
repository-code: 'https://github.com/MedVisBonn/eyeseg'
keywords:
- OCT
- Layer
- Segmentation
- Drusen
- AMD
- Biomarker
- Spectralis
- BM
- RPE
- EZ
license: MIT
commit: 094cca0029cd8b270e99112b778d0bb0aed528cd
version: v1.0.0
date-released: '2023-05-22'
preferred-citation:
authors:
- family-names: Morelle
given-names: Olivier
- family-names: Wintergerst
given-names: Maximilian W. M.
- family-names: Finger
given-names: Robert P.
- family-names: Schultz
given-names: Thomas
title: Accurate drusen segmentation in optical coherence tomography via order-constrained regression of retinal layer heights
type: article
doi: 10.1038/s41598-023-35230-4
date-published: "2023-05-19"
year: 2023
journal: Scientific Reports
abstract: "Drusen are an important biomarker for age-related macular degeneration (AMD). Their accurate segmentation based on optical coherence tomography (OCT) is therefore relevant to the detection, staging, and treatment of disease. Since manual OCT segmentation is resource-consuming and has low reproducibility, automatic techniques are required. In this work, we introduce a novel deep learning based architecture that directly predicts the position of layers in OCT and guarantees their correct order, achieving state-of-the-art results for retinal layer segmentation. In particular, the average absolute distance between our model's prediction and the ground truth layer segmentation in an AMD dataset is 0.63, 0.85, and 0.44 pixel for Bruch's membrane (BM), retinal pigment epithelium (RPE) and ellipsoid zone (EZ), respectively. Based on layer positions, we further quantify drusen load with excellent accuracy, achieving 0.994 and 0.988 Pearson correlation between drusen volumes estimated by our method and two human readers, and increasing the Dice score to 0.71 ± 0.16 (from 0.60 ± 0.23) and 0.62 ± 0.23 (from 0.53 ± 0.25), respectively, compared to a previous state-of-the-art method. Given its reproducible, accurate, and scalable results, our method can be used for the large-scale analysis of OCT data."