Embryo developmental stage classification method in embryo time sequence image

Abstract

The invention relates to an embryo developmental stage classification method in an embryo time sequence image. The method comprises the steps that M time sequence images to be detected in the embryonic development process are acquired and sequentially input into a single-input-multiple-output convolutional neural network, m probability sequences corresponding to m adjacent images to be detected ina one-to-one mode are obtained under input of each image to be detected, and m is smaller than M; based on all the m probability sequences, integrating is performed to obtain m probability sequencesof each to-be-detected image, and the m probability sequences are fused to obtain a probability fusion sequence of the to-be-detected image; and a matrix formed by the probability fusion sequences ofthe to-be-detected images is smoothed by adopting a dynamic programming method meeting monotonically increasing constraints, and a development stage corresponding to each to-be-detected image is identified. According to the method, the single-input multi-output convolutional neural network is adopted, integrated fusion processing is combined, single-input multi-output is converted into single-input single-output, and finally the development stage of each image is obtained by adopting a dynamic planning method, so that the classification accuracy is high, and the calculation complexity is low.

Description

technical field [0001] The invention belongs to the field of assisted reproduction, and more specifically relates to a method for classifying embryo development stages in embryo timing images. Background technique [0002] In the field of assisted reproduction, the cultivation, selection and transplantation of fertilized eggs are one of the key steps in determining whether infertile patients can become pregnant. During the cultivation of fertilized eggs, time-lapse technology is usually used to monitor the fertilized eggs regularly, and a large amount of time-series image data will be collected for each embryo. The time-lapse technology records the development process of embryos in real time by taking pictures of embryos at short intervals at regular intervals. At the final stage of fertilized egg selection, doctors can conveniently browse through the development process of fertilized eggs at one time, so as to score fertilized eggs and sort. In addition, time-lapse techno...

AI Technical Summary

Problems solved by technology

[0004] The invention provides a method for classifying embryonic developmental stages in time-series images of embryos, which is used to solve the technical problem of improving the classification accuracy of the developmental stages of the entire cycle of embryonic development with low computational complexity

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