With the continuous improvement of the accuracy requirements of clinical base or base tooth and denture,the design of denture neck edge is becoming thinner and thinner,and the presintering zirconia dioxide billet for ...With the continuous improvement of the accuracy requirements of clinical base or base tooth and denture,the design of denture neck edge is becoming thinner and thinner,and the presintering zirconia dioxide billet for denture making evacuation and low strength material mechanical characteristics make the certain probability of denture neck edge fragmentation and peeling in the cutting process.Based on this phenomenon,the abnormal wear is the main reason,and a method of high frequency ultrasonic time cleaning to reduce the fracture of the denture neck in actual cutting is proposed.展开更多
Panoramic radiographs can assist dentist to quickly evaluate patients’overall oral health status.The accurate detection and localization of tooth tissue on panoramic radiographs is the first step to identify patholog...Panoramic radiographs can assist dentist to quickly evaluate patients’overall oral health status.The accurate detection and localization of tooth tissue on panoramic radiographs is the first step to identify pathology,and also plays a key role in an automatic diagnosis system.However,the evaluation of panoramic radiographs depends on the clinical experience and knowledge of dentist,while the interpretation of panoramic radiographs might lead misdiagnosis.Therefore,it is of great significance to use artificial intelligence to segment teeth on panoramic radiographs.In this study,SWin-Unet,the transformer-based Ushaped encoder-decoder architecture with skip-connections,is introduced to perform panoramic radiograph segmentation.To well evaluate the tooth segmentation performance of SWin-Unet,the PLAGH-BH dataset is introduced for the research purpose.The performance is evaluated by F1 score,mean intersection and Union(IoU)and Acc,Compared with U-Net,Link-Net and FPN baselines,SWin-Unet performs much better in PLAGH-BH tooth segmentation dataset.These results indicate that SWin-Unet is more feasible on panoramic radiograph segmentation,and is valuable for the potential clinical application.展开更多
文摘With the continuous improvement of the accuracy requirements of clinical base or base tooth and denture,the design of denture neck edge is becoming thinner and thinner,and the presintering zirconia dioxide billet for denture making evacuation and low strength material mechanical characteristics make the certain probability of denture neck edge fragmentation and peeling in the cutting process.Based on this phenomenon,the abnormal wear is the main reason,and a method of high frequency ultrasonic time cleaning to reduce the fracture of the denture neck in actual cutting is proposed.
文摘Panoramic radiographs can assist dentist to quickly evaluate patients’overall oral health status.The accurate detection and localization of tooth tissue on panoramic radiographs is the first step to identify pathology,and also plays a key role in an automatic diagnosis system.However,the evaluation of panoramic radiographs depends on the clinical experience and knowledge of dentist,while the interpretation of panoramic radiographs might lead misdiagnosis.Therefore,it is of great significance to use artificial intelligence to segment teeth on panoramic radiographs.In this study,SWin-Unet,the transformer-based Ushaped encoder-decoder architecture with skip-connections,is introduced to perform panoramic radiograph segmentation.To well evaluate the tooth segmentation performance of SWin-Unet,the PLAGH-BH dataset is introduced for the research purpose.The performance is evaluated by F1 score,mean intersection and Union(IoU)and Acc,Compared with U-Net,Link-Net and FPN baselines,SWin-Unet performs much better in PLAGH-BH tooth segmentation dataset.These results indicate that SWin-Unet is more feasible on panoramic radiograph segmentation,and is valuable for the potential clinical application.
