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...
| المؤلفون الرئيسيون: | , , , , |
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| التنسيق: | مقال |
| اللغة: | English |
| منشور في: |
Nature Portfolio
2024-03-01
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| سلاسل: | Scientific Reports |
| الموضوعات: | |
| الوصول للمادة أونلاين: | https://doi.org/10.1038/s41598-024-57562-5 |