Image recognition method and server

The embodiment of the invention provides an image recognition method and a server. The method and the server can solve the problem that in the prior art, the accuracy is poor when a network model of an open source architecture is used for disease diagnosis. The image recognition method comprises the following steps: acquiring historical positron emission type computed tomography (PET) images of various types of brain diseases, and training a pre-constructed deep learning network based on the historical PET images to obtain a disease diagnosis model, the deep learning network comprises a plurality of layers of first convolutional networks based on M convolution kernels, at least two second convolutional networks and a full-connection network; and when a new PET image is received, identifying the new PET image based on the disease diagnosis model, and outputting a diagnosis result. 本发明实施例提供了一种图像识别方法及服务器，该方法和服务器能够解决现有技术中使用开源架构的网络模型来进行疾病诊断的准确性较差的问题。其中，图像识别方法包括：获取各个类型的脑部疾病的历史正电子发射型计算机断层显像PET图像，并基于历史PET图像对预先构建的深度学习