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: | , , , , |
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| 格式: | 文件 |
| 语言: | English |
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Nature Portfolio
2024-03-01
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| 丛编: | Scientific Reports |
| 主题: | |
| 在线阅读: | https://doi.org/10.1038/s41598-024-57562-5 |