Medical image classification method, model training method, computing device, and storage medium

An apparatus for classifying a medical image, the apparatus comprising:

• a memory storing instructions;
• and
• a processor in communication with the memory, wherein, when the processor executes the instructions, the processor is configured to cause the apparatus to:
• obtain a medical image data set,
• perform quality analysis on the medical image data set, to extract feature information of a medical image in the medical image data set, and
• classify the medical image data set based on the feature information and by using a pre-trained deep learning network for performing anomaly detection and classification, to obtain a classification result.

A non-transitory computer-readable storage medium, storing computer-readable instructions, wherein, the computer-readable instructions, when executed by a processor, are configured to cause the processor to perform:

• obtaining a medical image data set;
• performing quality analysis on the medical image data set, to extract feature information of a medical image in the medical image data set;
• and
• classifying the medical image data set based on the feature information and by using a pre-trained deep learning network for performing anomaly detection and classification, to obtain a classification result.