| Identifier |
20220213_nanos_posters_270 |
| Title |
Quantification and Visualization of Edema Patterns Seen in Papilledema Using a Deep-Learning Variational Auto-Encoder |
| Creator |
Jui-Kai Wang; Mona Garvin; Randy Kardon |
| Affiliation |
(JW) (RK) Dept. Ophthalmology, University of Iowa and VA Healthcare System, Iowa City, Iowa; (MG) Dept. Electrical and Computer Engineering, U. of Iowa/VA Healthcare System, Iowa City, Iowa |
| Subject |
High Intracranial Pressure/Headache; Diagnostic Tests (ERG, VER, OCT, HRT, mfERG, etc); Pseudotumor Cerebri |
| Description |
We trained a deep-learning variational autoencoder (VAE) to analyze spatial patterns of optic disc edema in different phases of papilledema which allowed the creation of a latent space visual 'map' defined by only two latent variables. The 15 x 15 map (225 image panels) depicts the continuum of spatial patterns that can be observed in papilledema across 125 subjects with multiple visits in the Idiopathic Intracranial Hypertension Treatment Trial (IIHTT) OCT-substudy. |
| 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: Idiopathic Intracranial Hypertension (IIH) |
| Collection |
Neuro-Ophthalmology Virtual Education Library: NANOS Annual Meeting Collection: https://novel.utah.edu/collection/nanos-annual-meeting-collection/ |
| Publisher |
North American Neuro-Ophthalmology Society |
| Holding Institution |
Spencer S. Eccles Health Sciences Library, University of Utah |
| Rights Management |
Copyright 2022. For further information regarding the rights to this collection, please visit: https://NOVEL.utah.edu/about/copyright |
| ARK |
ark:/87278/s6eb661s |
| Setname |
ehsl_novel_nam |
| ID |
2065088 |
| Reference URL |
https://collections.lib.utah.edu/ark:/87278/s6eb661s |
