WISE: whole-scenario embryo identification using self-supervised learning encoder in IVF
Journal of Assisted Reproduction and Genetics(2024)
摘要
To study the effectiveness of whole-scenario embryo identification using a self-supervised learning encoder (WISE) in in vitro fertilization (IVF) on time-lapse, cross-device, and cryo-thawed scenarios. WISE was based on the vision transformer (ViT) architecture and masked autoencoders (MAE), a self-supervised learning (SSL) method. To train WISE, we prepared three datasets including the SSL pre-training dataset, the time-lapse identification dataset, and the cross-device identification dataset. To identify whether pairs of images were from the same embryos in different scenarios in the downstream identification tasks, embryo images including time-lapse and microscope images were first pre-processed through object detection, cropping, padding, and resizing, and then fed into WISE to get predictions. WISE could accurately identify embryos in the three scenarios. The accuracy was 99.89
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关键词
In vitro fertilization,Non-conformance,Whole-scenario embryo identification,Witness,Self-supervised learning,Vision transformer
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