Accuracy of generative deep learning model for macular anatomy prediction from optical coherence tomography images in macular hole surgery

Abstract This study aims to propose a generative deep learning model (GDLM) based on a variational autoencoder that predicts macular optical coherence tomography (OCT) images following full-thickness macular hole (FTMH) surgery and evaluate its clinical accuracy. Preoperative and 6-month postoperati...

Бүрэн тодорхойлолт

Номзүйн дэлгэрэнгүй
Үндсэн зохиолчид: Han Jo Kwon, Jun Heo, Su Hwan Park, Sung Who Park, Iksoo Byon
Формат: Өгүүллэг
Хэл сонгох:English
Хэвлэсэн: Nature Portfolio 2024-03-01
Цуврал:Scientific Reports
Нөхцлүүд:
Онлайн хандалт:https://doi.org/10.1038/s41598-024-57562-5