The invention relates to the technical field of image recognition, and discloses an image
feature recognition method and
system applied to the early stage of
kidney diseases. According to the method, the features in the original ultrasonic image are extracted in parallel, and the
micro texture change and the macroscopic form information shown in the abnormal area can be captured respectively, so that the limitation of a traditional single-scale
feature extraction method in coping with diffusive and weak-saliency image features is overcome; the local
texture feature map and the
global structure feature map are analyzed, quantization and positioning of weak texture changes are achieved, priori knowledge is converted into objective indexes, pixel-
level fusion is carried out on a texture abnormal map and a region
importance weight map, and through the knowledge-guided and data-driven deep fusion method, the deep fusion of the texture abnormal map and the region
importance weight map is achieved. It is ensured that the finally recognized abnormal area is not only a statistical
outlier but also conforms to importance distribution of an
image structure, and high-precision automatic recognition of weak and diffuse features in the
kidney medical image is facilitated.