The embodiment of the invention discloses a classification method and device of a medical image. Firstly, division of training files and verification files is carried out, and then non-illness markervalues and illness marker values are added; in response to a training instruction on a classifier, the plurality of training files are used as input of an auto-encoder, convolution kernels used for classification training are generated through preprocessing the auto-encoder, and fine tuning is carried out on parameters in the classifier to obtain an optimal network structure according to the generated convolution kernels; and then, in response to a classification instruction of the classifier, the input to-be-classified medical image is classified according to the classifier obtaining the optimal network structure. An effective intelligent prediction model is established through a method of supervised learning, thus convolutional neural networks (CNN) can be applied to medical image classification, reference of assisted decision making is provided for medical staffs, and efficiency is improved while human resources are saved.
Classification method and device of medical image