The application discloses a liver
ultrasound contrast
lesion classification method based on multi-
modal information and
perfusion kinetics, and the method comprises the following steps: acquiring
video image data with
perfusion contrast images and standard gray-scale images and preprocessing, and structuring a clinical
data vector of a patient; identifying a
liver lesion ROI region and obtaining a TIC curve for analysis to obtain
blood flow kinetics key phase characteristics; based on a double-head input
time sequence classification model of the gray-scale images and the contrast images, first spatial characteristics and second spatial characteristics are extracted and fused to obtain visual fusion characteristics; a clinical
data vector is projected to an embedding space aligned with image characteristics to obtain a clinical
feature vector; finally, an explainability
heat map is obtained,
blood flow kinetics key phase characteristics are marked on the TIC curve, the most important clinical indicators in classification decision are listed according to category probability, and the summary is used as an auxiliary diagnosis result.