The invention belongs to the technical field of
image segmentation, and particularly relates to an intelligent segmentation method and
system for an
acute pancreatitis CT image, and the method comprises the steps: simulating a normal pancreatic CT image, carrying out the virtual
lesion generation, fusing a virtual CT image set with a real CT image, extracting the topological structure features of the
pancreatic tissue of the fused image, and carrying out the segmentation of the
pancreatic tissue; performing
unsupervised clustering on the topological structure image by adopting a topological
perception diffusion coacervation method, and distinguishing
pancreas and background regions; differentiated mechanical parameters are distributed to all areas of the preliminary segmentation
mask, and boundary deformation is corrected; carrying out fine correction on the pixels of the optimized
mask by adopting an entropy optimization threshold method; and according to the region segmentation
mask, automatically calculating a necrotic volume ratio and an exudation maximum sectional area, and outputting a region segmentation result. According to the method, a
virtual image is generated through fluid
diffusion, topological guide segmentation and mechanical correction are carried out, accurate partitioning and quantitative grading are achieved, and
clinical diagnosis is assisted.