The invention relates to the technical field of medical
image processing, in particular to a method and
system for identifying odontogenic jaw
cyst and tumor based on
deep learning, and the method comprises the steps: obtaining original jaw
CBCT image data, carrying out the preprocessing, and generating a combined
annotation data set containing
lesion types,
tooth root absorption form annotations and CT value annotations; constructing a multi-
branch neural
network model, and training the multi-
branch neural
network model by using the joint labeling
data set to obtain an odontogenic jaw
lesion recognition model; and obtaining jaw
CBCT image data of a target patient, inputting the jaw
CBCT image data into the odontogenic jaw
lesion recognition model, and outputting
lesion type classification results,
tooth root absorption forms and bone destruction volumes. The diagnosis capability of minimal lesions can be improved,
missed diagnosis is reduced, whole-process auxiliary diagnosis from qualitative diagnosis to quantitative analysis is realized, and the diagnosis speed is increased.