The invention provides an early-stage intelligent diagnosis method for
rheumatoid arthritis based on a multi-
modal medical image and
deep learning, and the method comprises the steps: carrying out the image cleaning and
standardization, automatic bone joint positioning and segmentation, and
quality control of a multi-
modal original data set, and obtaining a joint slice
library; performing intra-
modal self-supervised pre-training and cross-modal alignment representation, and then performing focus level detection and quantification to obtain a
lesion feature vector of each joint; performing joint diagram construction and quality
perception multi-modal fusion to obtain fusion feature representation, and performing weak supervision multi-instance learning and multi-task loss calculation based on the fusion feature representation to obtain an uncalibrated model; and carrying out model calibration and explainable output to obtain an intelligent diagnosis model. According to the method, the diagnosis time point can be advanced to the reversible
inflammation stage, interpretable evidence of patient-level decision and joint-level quantification is provided, the
engineering feasibility of small samples and multi-center generalization is considered, and the method has high clinical transformation potential.