AI RESEARCH
From Division to Decision: Leveraging Temporal Cell-Stage Segmentation for Embryo Transferability Prediction
arXiv CS.LG
•
ArXi:2605.18923v1 Announce Type: cross 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.