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...
| Main Authors: | , , , , |
|---|---|
| 格式: | Article |
| 語言: | English |
| 出版: |
Nature Portfolio
2024-03-01
|
| 叢編: | Scientific Reports |
| 主題: | |
| 在線閱讀: | https://doi.org/10.1038/s41598-024-57562-5 |