深度学习在体外受精胚胎优选中的应用  

Application of Deep Learning in Optimal Embryo Selection of In Vitro Fertilization

作　　者：霍文杰 王晓聪 彭飞 全松(审校)[1] HUO Wen-jie;WANG Xiao-cong;PENG Fei;QUAN Song(Reproductive Medicine Center,Department of Obstetrics and Gynecology,Nanfang Hospital,Southern Medical University,Guangzhou 510515,China;School of Public Health,Southern Medical University,Guangzhou 510515,China)

机构地区：[1]南方医科大学南方医院妇产科生殖医学中心,广州510515 [2]南方医科大学公共卫生学院

出　　处：《国际生殖健康／计划生育杂志》2023年第2期135-139,共5页Journal of International Reproductive Health/Family Planning

基　　金：国家自然科学基金(82171656);广州市科技计划项目(2023A04J2302)。

摘　　要：挑选移植胚胎对提高体外受精-胚胎移植周期成功率至关重要。当前最常用的挑选胚胎方法是胚胎形态学评估,其高度依赖于实验室技术人员的主观视觉印象和个人经验,影响胚胎优选的准确性和一致性。近年有学者尝试将深度学习算法引入移植胚胎的选择,基于大量人工标记的胚胎图像/视频建立质量评估和结局预测模型,发现深度学习模型具备客观、准确、高效及稳定等优点。综述深度学习模型优选胚胎研究现状,并与人工胚胎形态学评估和经典机器学习算法的性能进行比较,进一步探讨其在辅助生殖中的应用价值。The selection of transferred embryo is one of the most important factors in achieving successful pregnancy of in vitro fertilization-embryo transfer.At present,the most common method of embryo selection is visual evaluation of embryo morphology,which is highly dependent on subjective vision and personal experience of lab technicians.This method may affect the accuracy and consistency of optimal embryo selection.Recently,some studies have tried to introduce the deep learning algorithm into embryo selection.The deep learning model is developed to assess quality,and to predict outcome based on a large number of manually labeled embryo images and vedios.It has been found that the deep learning algorithm was objective,accurate,efficient and stable.This paper reviews the application of deep learning,as well as its research progress,in embryo selection,and compares deep learning with manual evaluation or classic machine learning algorithms,so as to provide a glimpse into the application value of deep learning in assisted reproduction.

关 键 词：体外受精 胚胎移植 深度学习 胚胎选择 胚胎质量 妊娠结局 

分 类 号：R714.8[医药卫生—妇产科学]