This invention relates to the interdisciplinary field of
assisted reproductive technology and
artificial intelligence, specifically to a
system and method for constructing an embryonic developmental trajectory map that integrates morphological features. By deeply integrating static morphological features with dynamic morphodynamic parameters, a more comprehensive panoramic map of embryonic development with richer information dimensions is constructed, overcoming the one-sidedness of single-dimensional assessment. Automated analysis of the map using an AI model reduces the influence of subjective human factors, enabling the discovery of subtle developmental patterns and potential differences that are difficult to discern with the
human eye, significantly improving the accuracy of selecting high-quality embryos. The provided developmental trajectory map allows embryologists to intuitively examine the entire developmental process of the
embryo and the performance of each key node, enhancing the
interpretability and credibility of the assessment process. Through more scientific
embryo selection, it is expected to improve
embryo implantation and
clinical pregnancy rates, and reduce multiple
pregnancy and
miscarriage rates.