A multimodality-based device for predicting the outcome of embryonic pregnancy

Abstract

The invention discloses a device for predicting embryo pregnancy results based on multimodality, which belongs to the field of medical artificial intelligence. Firstly, the image of the embryo developed to the blastocyst stage after in vitro fertilization and the corresponding pregnancy result are obtained, and the blastocyst and inner cells of the embryo are obtained. Three images of clumps and trophoblast cells, labeled with pregnancy results, annotated data, as raw data. Then use the Gaussian kernel function to smooth the image, remove part of the noise, and then normalize the image. Afterwards, data augmentation is performed on the image as input data. Image fusion of three images using a multimodal approach such that the input image contains features for the three evaluation aspects. Pass the fused image into ResNet‑50 for training, optimize the network according to the target label, and iterate until the training is complete. After having a model, before embryo transfer, take three images, which can be imported into the model to predict the pregnancy result, and the embryo with a high success rate can be selected according to the output result, which can improve the final pregnancy success rate.

Description

technical field [0001] The invention relates to the field of medical artificial intelligence, in particular to a multimodal-based embryo pregnancy outcome prediction device. Background technique [0002] The infertility rate in my country has climbed from 2.5%-3% 20 years ago to 12.5%-15%, and it is showing a trend of increasing and younger. According to statistics, in 2016, the number of infertility patients in my country has exceeded 5000 Ten thousand. On the other hand, the opening of the two-child policy has brought about a birth peak. In recent years, there are about 16 million newborns in my country every year, of which about 2-2.4 million newborns cannot be born due to infertility. This has directly led to the surge in demand and the expansion of the scale of the assisted reproductive market. [0003] Assisted reproductive technology mainly refers to artificial insemination and in vitro fertilization-embryo transfer (In Vitro Fertilization and Embryo Transfer, IVF-ET...

AI Technical Summary

Problems solved by technology

However, there is currently no system for efficient and accurate embryo pregnancy prediction using deep learning algorithms

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