Embryo pregnancy state intelligent prediction method and system

An intelligent prediction and embryo technology, applied in the field of embryo morphology and artificial intelligence, can solve the problems of low accuracy and poor real-time performance

Active Publication Date: 2020-10-16
WUHAN MUTUAL UNITED TECH CO LTD
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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 an

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  • Embryo pregnancy state intelligent prediction method and system
  • Embryo pregnancy state intelligent prediction method and system

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Embodiment Construction

[0048] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0049] During embryo development, the characteristics of debris, blastocoel, inner cell mass, and trophoblast become more and more complex over time, which poses challenges to the generalizability of the design algorithm.

[0050] The intelligent prediction method of embryonic pregnancy status proposed by the present invention, such as figure 1 shown, including the following steps:

[0051] 1) collecting images of embryos within D1-D6;

[0052] 2) Input the embryo image into the fragment ratio prediction network model, the blastocoel and inner cell mass grade prediction network model, and the trophoblast grade prediction network model;

[0053] 3) The fragment ratio prediction network model calculates and outputs the predicted fragment ratio of the embryo image, the blastocoel and inner cell mass grade prediction network model calcu...

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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...

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Application Information

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IPC IPC(8): G06K9/62
CPCG06V2201/03G06F18/241G06F18/29G06F18/214
Inventor 陈长胜谭威云新
Owner WUHAN MUTUAL UNITED TECH CO LTD
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