The application discloses a
uterus tumor
differential diagnosis method and
system based on multi-parameter
MRI imaging and belongs to the technical field of medical
image processing and
artificial intelligence diagnosis. The method aims at the problems existing in the current
uterus tumor MRI diagnosis, such as strong subjective dependence, insufficient utilization of multi-parameter information, unreasonable
feature screening and model construction. The method comprises the following steps: collecting T1WI, T2WI, T2
fat suppression sequence and DWI multi-parameter images; after format
standardization, deartifacting and Z-
score normalization, a model combining U-Net and attention mechanism is used to realize
automatic segmentation of the lesions; multi-dimensional features are extracted and the optimal subset is screened by ANOVA filtering-RFE-SVM packaging method; a stacking integrated model is constructed for training, and the output includes the differential results and confidence of ordinary
uterine fibroids, special type
uterine fibroids and uterine
sarcoma; the application integrates multi-parameter complementary information, improves the segmentation efficiency and feature quality, has strong model generalization ability and accurate diagnosis, is suitable for the actual situation of the scarcity of uterine
sarcoma cases, and provides an objective
diagnosis tool for clinical use.