用Transformer分析牛胚胎四天发育视频，提升移植成功率预测
From Division to Decision: Leveraging Temporal Cell-Stage Segmentation for Embryo Transferability Prediction
- 用时空变换器融合帧级特征与阶段表征，建模胚胎早期发育
- 在第4天预测胚胎可移植性，准确率优于现有方法
- 适合辅助生殖医学与动物育种领域研究者使用
准确选择牛胚胎是一项挑战，因当前实践依赖于受精后第7天单次专家评估，导致妊娠丢失率较高。时间延迟视频显微技术提供了早期发育的详细信息，但因运动模式复杂且分析耗时而难以利用。本文提出TransFACT，一种基于Transformer的框架，利用前四天的2D时间延迟视频建模早期发育阶段与胚胎可移植性。TransFACT结合帧级时序特征与阶段级表示，以发育阶段作为辅助监督信号，在第4天预测可移植性。实验表明，通过借鉴动作识别领域的现有方法，TransFACT在预测胚胎可移植性方面优于其竞争模型。
原文摘要 · Abstract (English)
Accurate selection of bovine embryos is a challenging task, as current practice relies on a single expert assessment on the seventh day after insemination, resulting in high rates of pregnancy loss. Time-lapse videomicroscopy provides detailed information on early development, but is difficult to exploit because of complex motion patterns and time-consuming analysis. We propose TransFACT, a transformer-based framework for modeling early developmental stages and embryo transferability using 2D time-lapse videos from the first four days of development. TransFACT combines frame-level temporal features with stage-level representations, using developmental stages as auxiliary supervision to predict transferability on day four. Our experiments demonstrate that TransFACT, by leveraging an existing method designed for action recognition, achieves superior performance than its competitor in predicting embryo transferability.
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