The invention belongs to the technical field of
medical treatment and pyradiomics, and particularly relates to a
gene heterogeneity visual quantification method in
glioma based on pyradiomics and a
system. The method of the invention comprises the steps of segmenting a
glioma magnetic
resonance image by means of an image segmenting network 3D U-net; performing predictive modeling on the integral
glioma IDH (
isocitrate dehydrogenase), namely performing high-flux characteristic extraction and characteristic screening on the image, and screening a characteristic combination which is most sensitive and most effective to
gene expression; performing heterogeneous modeling on the glioma IDH based on an image block, extracting a multi-dimensional data block of the glioma image, obtaining the IDH expression strength of each data block based on the integral predicting model; and finally forming the IDH distribution
visualization and
quantitative expression of the whole tumor. The method and thesystem have advantages of more accurately determining the prognosis and radiotherapy and
chemotherapy sensitivity of the patient, realizing
surgery resection and targeting treatment in heterogeneous atlas navigation, and realizing high
clinical value in improving
treatment effect of the patient and improving
survival prognosis.