Applying Neural Networks to Macular OCTA to Differentiate LHON Vasculature from Normal Vasculature

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Identifier 20210222_nanos_posters_143
Title Applying Neural Networks to Macular OCTA to Differentiate LHON Vasculature from Normal Vasculature
Creator William Sultan, Giulia Amore, Kashif Iqbal, Samuel Asanad, Rustum Karanji, Alfredo Sadun
Subject Diagnostic Tests (ERG, VER, OCT, HRT, mfERG, etc); Retina; Orbit/Ocular Pathology
Description Neural networks have the capacity to recognize patterns in data that are typically too complex for a human to make a determination. Using artificial intelligence, we are gaining the ability to discern the presence of optic neuropathy related mitochondrial disease using data based on the vasculature architecture in the retina.
Date 2021-02
Language eng
Format application/pdf
Type Text
Source 2021 North American Neuro-Ophthalmology Society Annual Meeting
Relation is Part of NANOS Annual Meeting 2021: Poster Session III: 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 2021. For further information regarding the rights to this collection, please visit: https://NOVEL.utah.edu/about/copyright
ARK ark:/87278/s6x40t6w
Context URL The NANOS Annual Meeting Neuro-Ophthalmology Collection: https://novel.utah.edu/collection/NAM/toc/
Contributor Primary William Sultan
Contributor Secondary Giulia Amore, Kashif Iqbal, Samuel Asanad, Rustum Karanji, Alfredo Sadun
Setname ehsl_novel_nam
ID 1675933
Reference URL https://collections.lib.utah.edu/ark:/87278/s6x40t6w
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