Embryo pregnancy state intelligent prediction method and system

Abstract

The invention discloses an embryo pregnancy state intelligent prediction method and system. The method comprises the steps of collecting embryo images within the time of D1 to D6; inputting the embryoimage into a fragment proportion prediction network model, a blastocyst cavity and inner cell mass grade prediction network model and a trophoblast grade prediction network model to calculate and outputting a predicted fragment proportion, a predicted blastocyst cavity proportion, a predicted inner cell mass grade and a predicted trophoblast grade of the embryo image; and inputting into an embryopregnancy rate state prediction machine learning model to calculate and output an embryo pregnancy rate prediction result. According to the intelligent prediction method and the system, the whole embryo development process is monitored, the embryo pregnancy rate is obtained through calculation by means of the comprehensive scoring function, manual intervention is not needed in the prediction process, and doctors can be helped to quickly and accurately judge embryo scores.

Description

technical field [0001] The invention relates to the technical fields of embryo morphology and artificial intelligence, in particular to an intelligent prediction method and system for embryo pregnancy status. Background technique [0002] The quality of embryo development directly affects the result of pregnancy rate. Embryologists rely on embryo morphology and genetics to distinguish the quality of embryos. Among them, the use of genetic methods to determine the quality of embryos requires extremely high experimental conditions. , and using embryo morphological information to complete embryo evaluation is a simple, fast and effective method. At present, most embryologists judge the quality of embryos by obtaining some important morphological feature changes in the embryo development process based on their long-term embryo observation experience, and use it as an important predictor of the success rate of embryo transfer in the later stage. in accordance with. Doctors usua...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to overcome the problems of low accuracy and poor real-time performance of traditional image analysis methods in the prior art in the acquisition of fragmented regions, calculation of blastocoel ratio, evaluation of inner cell mass and trophoblast grade, A method and system for intelligent detection of embryo pregnancy status is proposed, which can automatically complete the extraction and prediction of high-level features of fragments, blastocoel, inner cell mass and trophoblast, and realize the comprehensive prediction of embryo pregnancy status accurately and efficiently.

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