Conjunctival Bulbar Redness Extraction Pipeline for High-Resolution Ocular Surface Photography
To empower clinicians and researchers with a high-throughput workflow by standardized imaging combined with an analysis tool based on artificial intelligence to objectively determine an image-based redness score.
Authors
- Daniel Baumgarten (ORCID: https://orcid.org/0000-0001-6109-3368)
- Marco Augustin (ORCID: https://orcid.org/0000-0002-1019-0907)
- Vito Romano (ORCID: https://orcid.org/0000-0002-5148-7643)
- Philipp Ostheimer (ORCID: https://orcid.org/0009-0006-8544-287X)
- Arno Lins
- Bernhard Steger (ORCID: https://orcid.org/0000-0002-5316-4661)
- Lars Albert Helle
Institutions
- Innsbruck Medical University (AT)
- Universität Innsbruck (AT)
- UMIT - Private Universität für Gesundheitswissenschaften, Medizinische Informatik und Technik (AT)
- University of Brescia (IT)
Publication Details
- Journal
- Translational Vision Science & Technology
- Published
- 2025-01-09
- DOI
- https://doi.org/10.1167/tvst.14.1.6
- Citations
- 1
- Primary Topic
- Glaucoma and retinal disorders
- Type
- article
- Field-Weighted Citation Impact
- 1.71