Identifier |
20220213_nanos_posters_321 |
Title |
The Effect of Video Quality on Deep Learning Nystagmus Detection |
Creator |
Narayani Wagle; John Morkos; Jorge Otero-Millan; David Zee; Kemar Green |
Affiliation |
(NW) Johns Hopkins University, Baltimore, MD; (JM) (ZA) (KG) Johns Hopkins University School of Medicine, Baltimore, MD; (JOM) University of California, Berkeley |
Subject |
Diagnostic Tests (ERG, VER, OCT, HRT, mfERG, etc); Nystagmus; Ocular Manifestations of Vestibular Disorders; Ocular Motility |
Description |
Nystagmus identification and interpretation is a challenging endeavor for non-expert neuro-otologist and neuro-ophthalmologist. In video-based eye tracking, nystagmus detection traditionally relies on the ability to track pupil and generate appropriate waveforms. It has been shown that video frame rates less than 30Hz may limiting eye tracking nystagmus detection. |
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: New Diagnostic Measurement Techniques |
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/s6gn6nrq |
Context URL |
The NANOS Annual Meeting Neuro-Ophthalmology Collection: https://novel.utah.edu/collection/NAM/toc/ |
Setname |
ehsl_novel_nam |
ID |
2065342 |
Reference URL |
https://collections.lib.utah.edu/ark:/87278/s6gn6nrq |