使用视觉转换器进行先进的胚胎平分类: 连续时间延迟成像和低采样技术的整合: 一项回顾性研究
Muhammad Fauzan Avidiansyah1, Nining Handayani1, Tri Aprilliana1
1IRSI Research Centre, Jakarta, Indonesia.
Journal of human reproductive sciences
|January 21, 2026
概括
视觉转换器 (ViT) 结合时间延迟成像和随机下面抽样 (RUS) 改善了胚胎化分类. 这种方法提高了马赛克胚胎的准确性,这对于优化辅助生殖技术 (ART) 结果至关重要.
科学领域:
- 辅助生殖技术 (ART) 是一种辅助生殖技术.
- 计算生物学 计算生物学
- 遗传学 是一个遗传学.
背景情况:
- 准确的胚胎化鉴定对于成功的辅助生殖技术 (ART) 结果至关重要.
- 传统的深度学习模型在与阶级不平衡作斗争,特别是代表不充分的马赛克胚胎.
- 马赛克胚胎在 ploidy 分类中构成了重大挑战.
研究的目的:
- 通过视觉转换器 (ViT) 提高胚胎化分类的准确性.
- 将顺序时间延迟成像与ViT集成,以改善胚胎评估.
- 通过随机低抽样 (RUS) 来解决数据不平衡,特别是马赛克胚胎的代表性不足.
主要方法:
- 进行了对1020个胚胎细胞阶段时间延迟视频的回顾性分析.
- 定制的深度学习模型,特别是ViT-B/16和ViT-B/32,进行了微调.
- 应用了随机低样本 (RUS) 来创建一个平衡的数据集,每个类 (欧体,无体,马赛克) 17,000 个图像.
主要成果:
- 在平衡数据集上,ViT-B/16模型在二进制分类中达到0.84准确度,在多类分类中达到0.67准确度.
- 在不平衡的数据集上,性能显著下降到0.49,突显了RUS.的有效性.
- 随机低抽样显著提高了少数阶级的预测准确度,包括马赛克胚胎.
结论:
- 将ViT与顺序时差成像和RUS集成,为胚胎化分类提供了一个有希望的非侵入性方法.
- 这种方法提高了识别马赛克胚胎的准确性.
- 这些发现支持在ART中进行更明智的胚胎选择,可能提高成功率.
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