Apostolopoulos, Stefanos; Salas, Jazmín; Ordóñez, José L P; Tan, Shern Shiou; Ciller, Carlos; Ebneter, Andreas; Zinkernagel, Martin; Sznitman, Raphael; Wolf, Sebastian; De Zanet, Sandro; Munk, Marion R. (2020). Automatically Enhanced OCT Scans of the Retina: A proof of concept study. Scientific Reports, 10(1), p. 7819. Nature Publishing Group 10.1038/s41598-020-64724-8
|
Text
s41598-020-64724-8.pdf - Published Version Available under License Creative Commons: Attribution (CC-BY). Download (2MB) | Preview |
In this work we evaluated a postprocessing, customized automatic retinal OCT B-scan enhancement software for noise reduction, contrast enhancement and improved depth quality applicable to Heidelberg Engineering Spectralis OCT devices. A trained deep neural network was used to process images from an OCT dataset with ground truth biomarker gradings. Performance was assessed by the evaluation of two expert graders who evaluated image quality for B-scan with a clear preference for enhanced over original images. Objective measures such as SNR and noise estimation showed a significant improvement in quality. Presence grading of seven biomarkers IRF, SRF, ERM, Drusen, RPD, GA and iRORA resulted in similar intergrader agreement. Intergrader agreement was also compared with improvement in IRF and RPD, and disagreement in high variance biomarkers such as GA and iRORA.
Item Type: |
Journal Article (Original Article) |
|---|---|
Division/Institute: |
04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Ophthalmology 10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research |
UniBE Contributor: |
Tan, Shern Shiou, Ebneter, Andreas, Zinkernagel, Martin Sebastian, Sznitman, Raphael, Wolf, Sebastian (B), Munk, Marion |
Subjects: |
500 Science > 570 Life sciences; biology 600 Technology > 610 Medicine & health |
ISSN: |
2045-2322 |
Publisher: |
Nature Publishing Group |
Language: |
English |
Submitter: |
Marion Munk |
Date Deposited: |
19 May 2020 09:59 |
Last Modified: |
02 Mar 2023 23:33 |
Publisher DOI: |
10.1038/s41598-020-64724-8 |
PubMed ID: |
32385371 |
BORIS DOI: |
10.7892/boris.143997 |
URI: |
https://boris.unibe.ch/id/eprint/143997 |
Actions (login required)
 |
Edit item |