The invention relates to the technical field of
image segmentation, in particular to a medical
image processing method for tumor partition recognition, which comprises the following steps: acquiring a multi-
modal medical image, extracting gray features and adjusting image gray, recognizing tissue boundary and
metabolism features, grouping and generating tumor boundary response partitions, extracting heterogeneous nodes and classifying and labeling. Dividing a core area, an infiltration area and a
necrosis area, and generating a tumor functional
structure chart. According to the method, the gray frequency and the edge trend of the multi-
modal image are unified, the structure contrast is enhanced, the consistency of each
modal image in space and
gray level is ensured, the
information fusion integrity is improved, the gray, texture and
metabolism characteristics are combined, the density
mutation and
metabolism enhancement region is identified, and the boundary clear contour is constructed; boundary partitions are established through response direction consistency, the cross-modal discrimination ability is enhanced, texture and metabolic characteristics are fused to classify heterogeneous nodes, a core area, an infiltration area and a
necrosis area are divided, and functional partitions with clear expression and clear structures are generated.