The invention discloses a cervical cell image classification method based on a convolutional neural network. The method comprises the following steps: preparing a training sample, classifying the training sample to obtain eleven types of samples, constructing a convolutional neural network, inputting the training sample into a convolutional neural network model for training, iterating for a certain number of times, stopping training, and storing network weight parameters. When the method is used, a target image is segmented into a to-be-predicted area with cell nucleuses, and then weight parameters and a network structure obtained through training are loaded. The to-be-predicted area is input into the to-be-predicted area. A classification result can be obtained through calculation. The method improves the accuracy and efficiency of cervical cell diagnosis, and has strong adaptive capacity.
Cervical cell image classification method based on convolutional neural network