The invention discloses a multi-
modal feature fused
portal vein pressure gradient acquisition method and
system, and relates to the technical field of
portal vein pressure acquisition, and the method comprises the steps: S1, obtaining a CT image of a patient, and carrying out the preprocessing of the CT image, and obtaining the related
feature data of the CT image; s2, constructing a multi-
modal feature model based on liver blood vessels in the CT image; inputting the preprocessed CT image data, the related
feature data and the corresponding to-be-predicted
portal vein pressure gradient
label value into a model for training; and S3, inputting the preprocessed CT image data and the related
feature data into the trained model, and performing prediction to obtain a portal
vein pressure gradient value corresponding to the CT image. Through an innovative multi-
modal fusion architecture and a two-stage training strategy,
pathological characteristics of geometric structure information and physical parameter information of a three-dimensional model are fully utilized, and high-precision and high-robustness non-contact prediction of PPG values under the condition that only CT image
blood vessel model input exists is realized.