3D retinal imaging and measurement using light field technology.


Journal

Journal of biomedical optics
ISSN: 1560-2281
Titre abrégé: J Biomed Opt
Pays: United States
ID NLM: 9605853

Informations de publication

Date de publication:
12 2021
Historique:
received: 10 06 2021
accepted: 06 12 2021
entrez: 18 12 2021
pubmed: 19 12 2021
medline: 1 2 2022
Statut: ppublish

Résumé

Light-field fundus photography has the potential to be a new milestone in ophthalmology. Up-to-date publications show only unsatisfactory image quality, preventing the use of depth measurements. We show that good image quality and, consequently, reliable depth measurements are possible, and we investigate the current challenges of this novel technology. We investigated whether light field (LF) imaging of the retina provides depth information, on which structures the depth is estimated, which illumination wavelength should be used, whether deeper layers are measurable, and what kinds of artifacts occur. The technical setup, a mydriatic fundus camera with an LF imager, and depth estimation were validated by an eye model and in vivo measurements of three healthy subjects and three subjects with suspected glaucoma. Comparisons between subjects and the corresponding optical coherence tomography (OCT) measurements were used for verification of the depth estimation. This LF setup allowed for three-dimensional one-shot imaging and depth estimation of the optic disc with green light. In addition, a linear relationship was found between the depth estimates of the OCT and those of the setup developed here. This result is supported by the eye model study. Deeper layers were not measurable. If image artifacts can be handled, LF technology has the potential to help diagnose and monitor glaucoma risk at an early stage through a rapid, cost-effective one-shot technology.

Identifiants

pubmed: 34921542
pii: JBO-210183RR
doi: 10.1117/1.JBO.26.12.126002
pmc: PMC8678491
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

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Auteurs

Stefan Schramm (S)

Technische Universität Ilmenau, Institute of Biomedical Engineering and Informatics, Faculty of Comp, Germany.

Alexander Dietzel (A)

Technische Universität Ilmenau, Institute of Biomedical Engineering and Informatics, Faculty of Comp, Germany.

Dietmar Link (D)

Technische Universität Ilmenau, Institute of Biomedical Engineering and Informatics, Faculty of Comp, Germany.

Maren-Christina Blum (MC)

Technische Universität Ilmenau, Institute of Biomedical Engineering and Informatics, Faculty of Comp, Germany.

Sascha Klee (S)

Technische Universität Ilmenau, Institute of Biomedical Engineering and Informatics, Faculty of Comp, Germany.
Karl Landsteiner University of Health Sciences, Division Biostatistics and Data Science, Department, Austria.

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Classifications MeSH