Fully Automated Segmentation of Human Eyeball Using Three-Dimensional U-Net in T2 Magnetic Resonance Imaging

PURPOSE: To develop and validate a fully automated deep-learning-based tool for segmentation of the human eyeball using a three-dimensional (3D) U-Net, compare its performance to semiautomatic segmentation ground truth and a two-dimensional (2D) U-Net, and analyze age and sex differences in eyeball...

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Detalles Bibliográficos
Autores principales: Yang, Jin-Ju, Kim, Kyeong Ho, Hong, Jinwoo, Yeon, Yeji, Lee, Ji Young, Lee, Won June, Kim, Yu Jeong, Lee, Jong-Min, Lim, Han Woong
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/PMC10664726/
https://www.ncbi.nlm.nih.gov/pubmed/37975841
http://dx.doi.org/10.1167/tvst.12.11.22

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10664726/
https://www.ncbi.nlm.nih.gov/pubmed/37975841
http://dx.doi.org/10.1167/tvst.12.11.22

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