| Identifier |
20220213_nanos_posters_329 |
| Title |
Quantification of Optic Nerve Head Edema from Fundus Photographs Using Machine Learning |
| Creator |
Ana Banc |
| Affiliation |
Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania |
| Subject |
Diagnostic Tests (ERG, VER, OCT, HRT, mfERG, etc); Pseudotumor Cerebri; High Intracranial Pressure/Headache; Neuroimaging; Miscellaneous |
| Description |
Machine learning (ML) models trained on large datasets of fundus photographs can differentiate normal optic discs from those with papilledema, but ML has not been used to quantify the amount of swelling. We hypothesized: (1) ML learning can quantify the retinal nerve fiber layer thickness (RNFLT), total retinal thickness (TRT), and optic nerve head volume (ONHV) from fundus photographs; (2) this can be accomplished with a relatively small training dataset. |
| Date |
2022-02 |
| Language |
eng |
| Format |
application/pdf |
| Type |
Text |
| Source |
2022 North American Neuro-Ophthalmology Society Annual Meeting |
| Relation is Part of |
NANOS Annual Meeting 2022: Poster Session I: Ocular-Imaging |
| Collection |
Neuro-ophthalmology Virtual Education Library: NOVEL http://NOVEL.utah.edu |
| Publisher |
Spencer S. Eccles Health Sciences Library, University of Utah |
| Holding Institution |
North American Neuro-Ophthalmology Association. NANOS Executive Office 5841 Cedar Lake Road, Suite 204, Minneapolis, MN 55416 |
| Rights Management |
Copyright 2022. For further information regarding the rights to this collection, please visit: https://NOVEL.utah.edu/about/copyright |
| ARK |
ark:/87278/s6qxdszp |
| Context URL |
The NANOS Annual Meeting Neuro-Ophthalmology Collection: https://novel.utah.edu/collection/NAM/toc/ |
| Setname |
ehsl_novel_nam |
| ID |
2065349 |
| Reference URL |
https://collections.lib.utah.edu/ark:/87278/s6qxdszp |
