Disclosed in the present invention are a multi-view semi-supervised lymph node classification method and system, and a device. Image preprocessing is performed on an original gray-scale ultrasonic image of a lymph node, image reconstruction is performed on the preprocessed image by using a U-shaped neural network, weighted fusion is performed o obtain a multi-scale fused coarse-grained image feature, and coarse-grained feature representation learning is performed by using a semi-supervised mode; an ROI containing a node in the original gray-scale ultrasonic image is cut to obtain a fine-grained image, weighted processing is performed on the fine-grained image via a VGG16 to which a space and channel attention mechanism is added in different levels, then global average pooling is performed, features of different levels are output for combination to obtain a fine-grained fusion feature, multi-view information is obtained by fusing a coarse-grained view feature and a fine-grained view feature, so that the fusion feature can have both the environment information and the detail information of the node, more abundant and accurate description is obtained, accurate classification can be achieved, and classification accuracy is improved.
MULTI-VIEW SEMI-SUPERVISED LYMPH NODE CLASSIFICATION METHOD AND SYSTEM, AND DEVICE