2 results about "Embryonic growth?" patented technology

The utility model relates to a utensil for incubator temperature measurement, including dish main part, the inner bottom wall of dish main part is provided with the limiting structure, the dish mouth of dish main part top covers with lid body, the through -hole is set up in the lid body, and the position of through -hole and limiting structure is in vertical direction alignment setting, limiting structure includes at least two's limit snap ring, one's limit ring and a plurality of support column, and the limit gap is formed between adjacent two support columns, the bottom of a plurality of support columns is fixed in the inner bottom wall of dish main part, and the top of a plurality of support columns is fixed one's limit ring, and two's limit snap ring is fixed in the inner side wall of limit ring through respective connecting block. Staff can accurately measure the actual temperature in the drawer type incubator through the external temperature measuring meter without opening the drawer type incubator. According to the measurement actual result, can ensure whether the culture temperature meets the temperature required for embryo growth.

The present invention discloses a method and system for predicting the embryonic growth stage based on self-supervised learning, which includes the following steps: collecting embryonic images at different growth stages as a training set, and dividing each embryonic image in the training set into a number of blocks of the same size; randomly selecting half of the blocks in each embryonic image for masking to obtain a masked training set; constructing a prediction model including an encoder and a decoder, where the encoder extracts a feature sequence from the masked training set, and the decoder reconstructs the embryonic image according to the feature sequence; using multiple weighted combined kernel functions as the loss function of the prediction model, adjusting the weight of each kernel function through cross-validation and gradient descent, and optimizing the parameters of the prediction model by backpropagation to obtain an optimal prediction model; inputting the embryonic image to be predicted into the optimal prediction model to obtain the prediction result of the embryonic growth stage.