Predicting OCT biological marker localization from weak annotations.

Gamazo Tejero, Javier; Márquez Neila, Pablo; Kurmann, Thomas Kevin; Gallardo, Mathias; Zinkernagel, Martin; Wolf, Sebastian; Sznitman, Raphael (2023). Predicting OCT biological marker localization from weak annotations. Scientific Reports, 13(1), p. 19667. Nature Publishing Group 10.1038/s41598-023-47019-6

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Recent developments in deep learning have shown success in accurately predicting the location of biological markers in Optical Coherence Tomography (OCT) volumes of patients with Age-Related Macular Degeneration (AMD) and Diabetic Retinopathy (DR). We propose a method that automatically locates biological markers to the Early Treatment Diabetic Retinopathy Study (ETDRS) rings, only requiring B-scan-level presence annotations. We trained a neural network using 22,723 OCT B-Scans of 460 eyes (433 patients) with AMD and DR, annotated with slice-level labels for Intraretinal Fluid (IRF) and Subretinal Fluid (SRF). The neural network outputs were mapped into the corresponding ETDRS rings. We incorporated the class annotations and domain knowledge into a loss function to constrain the output with biologically plausible solutions. The method was tested on a set of OCT volumes with 322 eyes (189 patients) with Diabetic Macular Edema, with slice-level SRF and IRF presence annotations for the ETDRS rings. Our method accurately predicted the presence of IRF and SRF in each ETDRS ring, outperforming previous baselines even in the most challenging scenarios. Our model was also successfully applied to en-face marker segmentation and showed consistency within C-scans, despite not incorporating volume information in the training process. We achieved a correlation coefficient of 0.946 for the prediction of the IRF area.

Item Type:

Journal Article (Original Article)

Division/Institute:

10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - AI in Medical Imaging Laboratory
04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Ophthalmology

UniBE Contributor:

Gamazo Tejero, Angel Javier, Márquez Neila, Pablo, Kurmann, Thomas Kevin, Gallardo, Mathias, Zinkernagel, Martin Sebastian, Wolf, Sebastian (B), Sznitman, Raphael

Subjects:

500 Science > 570 Life sciences; biology
600 Technology > 610 Medicine & health

ISSN:

2045-2322

Publisher:

Nature Publishing Group

Language:

English

Submitter:

Pubmed Import

Date Deposited:

13 Nov 2023 14:43

Last Modified:

26 Nov 2023 02:26

Publisher DOI:

10.1038/s41598-023-47019-6

PubMed ID:

37952011

BORIS DOI:

10.48350/188809

URI:

https://boris.unibe.ch/id/eprint/188809

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