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dc.contributor.author
Hofer, Dominik
dc.contributor.author
Schmidt Erfurth, Ursula
dc.contributor.author
Orlando, José Ignacio
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dc.contributor.author
Goldbach, Felix
dc.contributor.author
Gerendas, Bianca S.
dc.contributor.author
Seeböck, Philipp
dc.date.available
2023-10-27T18:31:35Z
dc.date.issued
2022-04
dc.identifier.citation
Hofer, Dominik; Schmidt Erfurth, Ursula; Orlando, José Ignacio; Goldbach, Felix; Gerendas, Bianca S.; et al.; Improving foveal avascular zone segmentation in fluorescein angiograms by leveraging manual vessel labels from public color fundus pictures; Optica Publishing Group; Biomedical Optics Express; 13; 5; 4-2022; 2566-2580
dc.identifier.issn
2156-7085
dc.identifier.uri
http://hdl.handle.net/11336/216268
dc.description.abstract
In clinical routine, ophthalmologists frequently analyze the shape and size of the foveal avascular zone (FAZ) to detect and monitor retinal diseases. In order to extract those parameters, the contours of the FAZ need to be segmented, which is normally achieved by analyzing the retinal vasculature (RV) around the macula in fluorescein angiograms (FA). Computer-aided segmentation methods based on deep learning (DL) can automate this task. However, current approaches for segmenting the FAZ are often tailored to a specific dataset or require manual initialization. Furthermore, they do not take the variability and challenges of clinical FA into account, which are often of low quality and difficult to analyze. In this paper we propose a DL-based framework to automatically segment the FAZ in challenging FA scans from clinical routine. Our approach mimics the workflow of retinal experts by using additional RV labels as a guidance during training. Hence, our model is able to produce RV segmentations simultaneously. We minimize the annotation work by using a multi-modal approach that leverages already available public datasets of color fundus pictures (CFPs) and their respective manual RV labels. Our experimental evaluation on two datasets with FA from 1) clinical routine and 2) large multicenter clinical trials shows that the addition of weak RV labels as a guidance during training improves the FAZ segmentation significantly with respect to using only manual FAZ annotations.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Optica Publishing Group
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Image quality
dc.subject
Image resolution
dc.subject
Image noise
dc.subject
Laser scanning
dc.subject.classification
Ciencias de la Computación
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dc.subject.classification
Ciencias de la Computación e Información
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dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
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dc.title
Improving foveal avascular zone segmentation in fluorescein angiograms by leveraging manual vessel labels from public color fundus pictures
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2023-10-26T15:22:03Z
dc.journal.volume
13
dc.journal.number
5
dc.journal.pagination
2566-2580
dc.journal.pais
Estados Unidos
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dc.journal.ciudad
Washington D.C
dc.description.fil
Fil: Hofer, Dominik. Medizinische Universität Wien; Austria
dc.description.fil
Fil: Schmidt Erfurth, Ursula. Medizinische Universität Wien; Austria
dc.description.fil
Fil: Orlando, José Ignacio. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Medizinische Universität Wien; Austria
dc.description.fil
Fil: Goldbach, Felix. Medizinische Universität Wien; Austria
dc.description.fil
Fil: Gerendas, Bianca S.. Medizinische Universität Wien; Austria
dc.description.fil
Fil: Seeböck, Philipp. Medizinische Universität Wien; Austria
dc.journal.title
Biomedical Optics Express
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://opg.optica.org/boe/fulltext.cfm?uri=boe-13-5-2566&id=471027
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1364/BOE.452873
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