Image analysis method, microscope video stream processing method, and related apparatus

A computing device for performing medical diagnosis using a microscope, comprising:

• one or more processors;
• and
• memory storing one or more programs for execution by the one or more processors, the one or more programs comprising instructions for:
• extracting video frames from a medical image video stream captured by the microscope that includes at least two pathological-section-based video frames;
• identifying single-frame image features in the video frames;
• mapping the single-frame image features into single-frame diagnostic classification results;
• performing classification mapping based on a video stream feature sequence that comprises the single-frame image features and the single-frame diagnostic classification results, the classification mapping comprising:
• performing a convolution operation on the video stream feature sequence through a preset convolutional layer;
• obtaining a convolution result in accordance with the convolution operation;
• and
• performing fully connected mapping on the convolution result through a preset fully connected layer;
• obtaining operation information of the microscope corresponding to the capturing of the medical image video stream;
• performing the classification mapping based on the operation information of the microscope and the video stream feature sequence;
• and
• determining a target diagnostic classification result corresponding to the medical image video stream and in accordance with the classification mapping.

A non-transitory computer-readable storage medium storing computer instructions that, when executed by one or more processors of a computing device for performing medical diagnosis using a microscope, cause the one or more processors to perform operations comprising:

• extracting video frames from a medical image video stream captured by the microscope that includes at least two pathological-section-based video frames;
• identifying single-frame image features in the video frames;
• mapping the single-frame image features into single-frame diagnostic classification results;
• performing classification mapping based on a video stream feature sequence that comprises the single-frame image features and the single-frame diagnostic classification results, the classification mapping comprising:
• performing a convolution operation on the video stream feature sequence through a preset convolutional layer;
• obtaining a convolution result in accordance with the convolution operation;
• and
• performing fully connected mapping on the convolution result through a preset fully connected layer;
• obtaining operation information of the microscope corresponding to the capturing of the medical image video stream;
• performing the classification mapping based on the operation information of the microscope and the video stream feature sequence;
• and
• determining a target diagnostic classification result corresponding to the medical image video stream and in accordance with the classification mapping.