Dental Age Estimation Based on X-ray Images

Chronological age estimation using panoramic dental X-ray images is an essential task in forensic sciences.Various statistical approaches have proposed by considering the teeth and mandible.However,building automated dental age estimation based on machine learning techniques needs more research efforts.In this paper,an automated dental age estimation is proposed using transfer learning.In the proposed approach,features are extracted using two deep neural networks namely,AlexNet and ResNet.Several classifiers are proposed to perform the classification task including decision tree,k-nearest neighbor,linear discriminant,and support vector machine.The proposed approach is evaluated using a number of suitable performance metrics using a dataset that contains 1429 dental X-ray images.The obtained results show that the proposed approach has a promising performance.

Comparing the accuracy of Demirjian and Nolla methods and establishing a new method for dental age estimation in northeastern Chinese children

Dental age estimation plays an important role in the field of clinic medicine and forensic medicine.The Demirjian and Nolla methods are common scoring methods for dental age estimation but there was no research about the comparison of accuracy of these two methods in northeastern Chinese children.Hence,in this study,we compared the accuracy of these two methods to explore more suitable method for our studied population.We collected 535 orthopantomograms from northern Chinese children aged from 6 to 15 years and divided them into training dataset and testing dataset according to the ratio of 7:3.The dental age of training dataset were estimated using Demirjian and Nolla methods,respectively.The results suggested that the mean differences of these two methods were 0.24 and−0.40 years,and mean absolute difference were 0.65 and 0.59 years.Then to further improve the accuracy of dental age assessment,the new improved formulas and dental age conversion tables were established after analyzing the relationship between the sum scores based on Nolla method and chronology age in training dataset.According to the new method used in testing dataset,the minimum value of mean difference(0.00)and mean absolute difference(0.49)were obtained,which are largely smaller than that of Demirjian and Nolla methods.The new developed method and dental age conversion scales may be more suitable dental age estimation method for northeastern Chinese children.

Application of Cameriere’s method for dental age estimation in children in South China

The aim of this study was to evaluate the applicability of Cameriere’s European formula for age estimation in children in South China and to adapt the formula to establish a more suitable formula for these children.Moreover,the performance of dental age estimation based on Cameriere’s method combining the developmental information of permanent teeth(PT)and third molar(TM)was also analysed.Orthopantomographs of 720 healthy children in Group A,and orthopantomographs of 320 children and 280 subadults in Group B were assessed.The samples of Group A were divided into training dataset 1 and test dataset 1,and the samples of Group B were also divided into training dataset 2 and test dataset 2.A South China-specific formula was established based on the training dataset 1,and the comparison of accuracy between the Cameriere’s European formula and the South China-specific formula was conducted with the test dataset 1.Additionally,a PT regression model,a TM regression model,and a combined regression model(PTþTM)were established based on the training dataset 2,and the performance of these three models were validated on the test dataset 2.The Cameriere’s European formula underestimated chronological age with a mean difference(ME)of-0.47±1.11 years in males and-0.69±1.19 years in females.However,the South China-specific formula underestimated chronological age,with a mean difference(ME)of-0.02±0.71 years in males and-0.14±0.73 years in females.Compared with PT model and TM model,the PT and TM combined model obtained the smallest root mean square error(RMSE)of 1.29 years in males and 0.93 years in females.In conclusion,the South China-specific formula was more suitable for assessing the dental age of children in South China,and the PT and TM combined model can improve the accuracy of dental age estimation in children.

Prevalence and Years Lived with Disability for Dental Caries among Children Aged 0-14 Years in China, 1990-2016

The estimate of dental caries among Chinese children at the microscale level using standard methodology remains unclear. In this study, we assessed and analyzed the disease burden of childhood dental caries in China by extracting data from the Global Burden of Disease, Injuries, and Risk Factors Study 2016 （GBD 2016）. In 2016, the number of cases, prevalence, years lived with disability （YLD）, and age-standardized YLD rate of dental caries was 93.0 million, 43.0%, 32,200 person years, and 14.8 per 100,000, respectively. Across 33 provincial units, the disease burden was highest in Hubei （YLD rate 28.6 per 100,000）, lowest in Macao （9.1 per 100,000）, while geographical clustering was not observed. Compared with 1990, the prevalence in 2016 decreased from 46.8% to 43.0%, and the YLD rate decreased from 16.5 per 100,000 to 14.8 per 100,000. Given the slight decrease in dental caries burden, the prevalence and disease burden remained high among Chinese children. Strategies for addressing the spatial inequity of childhood dental caries require geographical targeting.