State Detection And Pathological Analysis Of Tooth Based On Dental X-Ray Image

Dental health seriously affects people's physical and mental health.However,due to the shortage of oral medical resources in China,most people are still suffering from dental diseases.In dentistry,X-ray images are used to examine the condition of bone structures in the teeth,gums,jaws,and mouth.While the lack of sufficient automatic resources to assist diagnosis,the analysis of dental X-ray images mainly depends on the experience and visual perception of the dentist.From the perspective of image processing,deep learning and digital image processing technology were used in this paper to process dental panoramic X-ray images to realize dental status detection and pathological analysis,so as to assist dentists in the diagnosis of dental disease.For the dental panoramic X-ray image data,we have used the instance segmentation model to extract the tooth position,shape and other information of each tooth firstly.Specifically,an improved Mask R-CNN model has been proposed,which improved the segmentation performance of the network through the skip-connection and the SE module,reaching an accuracy rate of more than 90%,and realized the fusion extraction of tooth semantic,position and category information.Then,for the extracted single tooth information,a fine-grained image classification model has been constructed to realize the classification of dental diseases.In particular,a bilinear attention model has been proposed,which combined the advantages of fine-grained features and visual attention,and achieved a classification accuracy of 96%,and completed the classification of healthy teeth,dental caries,periodontal disease,wisdom teeth and other teeth.Finally,for the identified dental diseases,the digital image processing technology has been used to provide pathological analysis to help doctors determine the diagnosis and treatment plan.This part mainly involves the analysis of periodontal disease and dental caries.For periodontal disease,the tooth exposure ratio was calculated and analyzed.And for caries,the texture feature analysis based on gray co-occurrence matrix was used.The results showed that the tooth exposure ratio had a significant effect on the distinguish between healthy teeth from periodontal disease,while the texture characteristics had a less significant effect on the different of healthy teeth,periodontal disease and dental caries.This dissertation provided a complete set of automatic analysis process of dental X-ray images,which could help doctors avoid the missed diagnosis and misdiagnosis during the diagnosis and treatment of dental diseases.It also has a certain significance for the implementation of computer technology in the field of intelligent medical services.