The invention relates to the technical field of
deep learning, and discloses a caries automatic classification auxiliary decision-making
system, which comprises a controller, an
image acquisition module, an auxiliary display module, an
image labeling module, an
image segmentation module, a
disease identification module, a
disease extraction module and a classification storage module. An
image segmentation module carries out tooth identification and segmentation on the labeled original image by adopting an improved
Mask R-CNN to obtain the form and position of each tooth, and the form and position of each tooth are superposed on the original image to serve as an identification image; and the
disease identification module is used for carrying out dental caries, periapical
periodontitis, root
bifurcation lesion and
impacted tooth identification on the identification image by adopting YOLO-Teth. According to the method, the form and the position of each tooth are obtained through the
Mask R-CNN model, meanwhile, tooth lesions are identified through the YOLO-Teth
network model, various oral lesions can be identified, the identification accuracy is improved, finally, disease images are displayed and stored in a classified mode, an auxiliary diagnosis means is provided for dentists, and the actual requirements of
clinical diagnosis are met.