Deep Learning Model for Static Ocular Torsion Detection Using Synthetically Generated Fundus Images

PURPOSE: The objective of the study is to develop deep learning models using synthetic fundus images to assess the direction (intorsion versus extorsion) and amount (physiologic versus pathologic) of static ocular torsion. Static ocular torsion assessment is an important clinical tool for classifyin...

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Detalles Bibliográficos
Autores principales: Wang, Chen, Bai, Yunong, Tsang, Ashley, Bian, Yuhan, Gou, Yifan, Lin, Yan X., Zhao, Matthew, Wei, Tony Y., Desman, Jacob M., Taylor, Casey Overby, Greenstein, Joseph L., Otero-Millan, Jorge, Liu, Tin Yan Alvin, Kheradmand, Amir, Zee, David S., Green, Kemar E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Association for Research in Vision and Ophthalmology 2023
Materias:
Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9840445/
https://www.ncbi.nlm.nih.gov/pubmed/36630147
http://dx.doi.org/10.1167/tvst.12.1.17

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9840445/
https://www.ncbi.nlm.nih.gov/pubmed/36630147
http://dx.doi.org/10.1167/tvst.12.1.17

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