Dental age estimation based on pulp chamber/crown volume ratio measured on CBCT images in a Spanish population

Age Estimation Using the Pulp-to-Tooth Area Ratio in an Indian Population Using Cone-Beam Computerised Tomography (CBCT): A Retrospective Study

BACKGROUND

Age estimation, whether for living or deceased individuals, is crucial in forensic sciences. Traditionally, the pulp-to-tooth area ratio determined from periapical radiographs has been employed as a non-invasive method for estimating age. Cone-beam computed tomography (CBCT) represents a newer technique, providing three-dimensional images of teeth in living individuals.

AIM

This study aims to estimate age using the pulp-to-tooth area ratio of four teeth (the permanent maxillary central incisor, lateral incisor, canine, and first premolar.

STUDY DESIGN

The study included ninety subjects ranging in age from 18 to 70 years.

CONCLUSION

This study concluded that the correlation between actual age and estimated age varied across different tooth types. There was a strong positive correlation between the maxillary right central incisor and maxillary right canine tooth, while the maxillary left canine tooth exhibited a slightly weaker but still positive correlation. This indicates that the maxillary right central incisor and maxillary right canine tooth are the most reliable for estimating age. Additionally, the study found that the linear regression results for estimating age based on the pulp-to-tooth area ratio, categorised by sex and each type of tooth, showed strong associations between age and the ratio for the maxillary left central incisor and maxillary left canine teeth in males, and for the maxillary left central incisor in females.

A potential novel technique for measurement of pulp volume on periapical radiography: A pilot study

Pulp volume can be assessed during dental treatment. Three-dimensional imaging techniques are not routinely used for this purpose because of high radiation doses. This study aimed to develop a novel method to measure pulp volume using periapical radiography. In this study, cone-beam computed tomography (CBCT) was used as a reference method. Periapical radiography and CBCTs obtained from the same patients (n = 32) were recorded. Pulp volume was determined by observing the density differences between the pulp and peripheral structures using ImageJ. A method of graph and volume calculation was developed for each tooth. The Shapiro-Wilk test and Mann-Whitney U test were used to show normality and non-normal distributions. The Bland-Altman plot was used to show the scattering of the mean versus difference values of the measurements of the two methods used to calculate the pulp volume. Normality was evaluated using the Shapiro-Wilk test. CBCT measurements are normally distributed (p = 0.307), while ImageJ is not normally distributed (p = 0.027). Therefore, the mean difference between the two groups was analyzed using the nonparametric Mann-Whitney U test. There was a statistically significant difference between the CBCT and ImageJ measurements (p = 0.01). According to Spearman's correlation analysis, the results obtained from the novel method were moderately correlated with those obtained from the reference method (r = 0.444). The results of this study indicated that a novel method-based Java software can be used to calculate pulp volume using low-dose radiation containing periapical radiography.

Dental age assessment in the living: a comparison of two common stage classifications for assessing radiographic visibility of the root canals in mandibular third molars

After dentition is complete, degenerative tooth characteristics can be used for dental age assessment. Radiological assessment of the visibility of the root canals of the mandibular third molars in dental panoramic radiographs (DPRs) is known to be one such suitable feature. Essentially, two different stage classifications are available for evaluating the visibility of the root canals of mandibular third molars in the DPR. The aim of this study was to determine if one method outperforms the other. Therefore, the 2010 method of Olze et al. was directly compared to the 2017 method of Lucas et al. in the 2020 modification of Al Qattan et al. To this end, 233 DPRs from 116 females and 117 males aged 20.0 to 40.9 years were evaluated by three independent experienced examiners. In addition, one examiner ran two independent evaluations. Correlation between age and stage was investigated, and the inter- and intra-rater reliability was estimated for both methods. Correlation between age and stage was higher with the Olze method (Spearman rho 0.388 [95% CI 0.309, 0.462], males and 0.283 [95% CI 0.216, 0.357], females) than the Lucas method (0.212 [95% CI 0.141, 0.284], males and 0.265 [95% CI 0.193, 0.340], females). The intra-rater repeatability of the Olze method (Krippendorff's α = 0.576 [95% CI 0.508, 0.644], males and α = 0.592 [95% CI 0.523, 0.661], females) was greater than that for the Lucas method (intra-rater α = 0.422 [95% CI 0.382, 0.502], males and α = 0.516 [95% CI 0.523, 0.661], females). Inter-rater reproducibility was also greater for the Olze method (α = 0.542 [95% CI 0.463, 0.620], males and α = 0.533 [95% CI 0.451, 0.615], females) compared to the Lucas method (α = 0.374 [95% CI 0.304, 0.443], males and α = 0.432 [95% CI 0.359, 0.505], females). The method of Olze et al. was found to present marginal advantages to the Lucas et al. method across all examinations and may be a more appropriate method for application in future studies.

Age estimation based on 3D pulp segmentation of first molars from CBCT images using U-Net

OBJECTIVE

To train a U-Net model to segment the intact pulp cavity of first molars and establish a reliable mathematical model for age estimation.

METHODS

We trained a U-Net model by 20 sets of cone-beam CT images and this model was able to segment the intact pulp cavity of first molars. Utilizing this model, 239 maxillary first molars and 234 mandibular first molars from 142 males and 135 females aged 15-69 years old were segmented and the intact pulp cavity volumes were calculated, followed by logarithmic regression analysis to establish the mathematical model with age as the dependent variable and pulp cavity volume as the independent variable. Another 256 first molars were collected to estimate ages with the established model. Mean absolute error and root mean square error between the actual and the estimated ages were used to assess the precision and accuracy of the model.

RESULTS

The dice similarity coefficient of the U-Net model was 95.6%. The established age estimation model was [Formula: see text] (V is the intact pulp cavity volume of the first molars). The coefficient of determination (R2), mean absolute error and root mean square error were 0.662, 6.72 years, and 8.26 years, respectively.

CONCLUSION

The trained U-Net model can accurately segment pulp cavity of the first molars from three-dimensional cone-beam CT images. The segmented pulp cavity volumes could be used to estimate the human ages with reasonable precision and accuracy.

Dental age estimation in Indonesian adults: An investigation of the maxillary canine pulp-to-tooth volume ratio using cone-beam computed tomography

Purpose

This study was performed to develop a linear regression model using the pulp-to-tooth volume ratio (PTVR) ratio of the maxillary canine, assessed through cone-beam computed tomography (CBCT) images, to predict chronological age (CA) in Indonesian adults.

Materials and Methods

A sample of 99 maxillary canines was collected from patients between 20 and 49.99 years old. These samples were obtained from CBCT scans taken at the Universitas Padjadjaran Dental Hospital in Indonesia between 2018 and 2022. Pulp volume (PV) and tooth volume (TV) were measured using ITK-SNAP, while PTVR was calculated from the PV/TV ratio. Using RStudio, a linear regression was performed to predict CA using PTVR. Additionally, correlation and observer agreement were assessed.

Results

The PTVR method demonstrated excellent reproducibility, and a significant correlation was found between the PTVR of the maxillary canine and CA (r=-0.74, P<0.01). The linear regression analysis showed an R2 of 0.58, a root mean square error of 5.85, and a mean absolute error of 4.31.

Conclusion

Linear regression using the PTVR can be effectively applied to predict CA in Indonesian adults between 20 and 49.99 years of age. As models of this type can be population-specific, recalibration for each population is encouraged. Additionally, future research should explore the use of other teeth, such as molars.

A systematic overview of dental methods for age assessment in living individuals: from traditional to artificial intelligence-based approaches

Dental radiographies have been used for many decades for estimating the chronological age, with a view to forensic identification, migration flow control, or assessment of dental development, among others. This study aims to analyse the current application of chronological age estimation methods from dental X-ray images in the last 6 years, involving a search for works in the Scopus and PubMed databases. Exclusion criteria were applied to discard off-topic studies and experiments which are not compliant with a minimum quality standard. The studies were grouped according to the applied methodology, the estimation target, and the age cohort used to evaluate the estimation performance. A set of performance metrics was used to ensure good comparability between the different proposed methodologies. A total of 613 unique studies were retrieved, of which 286 were selected according to the inclusion criteria. Notable tendencies to overestimation and underestimation were observed in some manual approaches for numeric age estimation, being especially notable in the case of Demirjian (overestimation) and Cameriere (underestimation). On the other hand, the automatic approaches based on deep learning techniques are scarcer, with only 17 studies published in this regard, but they showed a more balanced behaviour, with no tendency to overestimation or underestimation. From the analysis of the results, it can be concluded that traditional methods have been evaluated in a wide variety of population samples, ensuring good applicability in different ethnicities. On the other hand, fully automated methods were a turning point in terms of performance, cost, and adaptability to new populations.

Automatic Pulp and Teeth Three-Dimensional Modeling of Single and Multi-Rooted Teeth Based on Cone-Beam Computed Tomography Imaging: A Promising Approach With Clinical and Therapeutic Outcomes

Background Cone-beam computed tomography (CBCT) imaging offers high-quality three-dimensional (3D) acquisition with great spatial resolution, given by the use of isometric voxels, when compared with conventional computed tomography (CT). The current literature supports a median reduction of 76% (up to 85% reduction) of patients' radiation exposure when imaged by CBCT versus CT. Clinical applications of CBCT imaging can benefit both medical and dental professions. Because these images are digital, the use of algorithms can facilitate the diagnosis of pathologies and the management of patients. There is pertinence to developing rapid and efficient segmentation of teeth from facial volumes acquired with CBCT. Methodology In this paper, a segmentation algorithm using heuristics based on pulp and teeth anatomy as a pre-personalized model is proposed for both single and multi-rooted teeth. Results A quantitative analysis was performed by comparing the results of the algorithm to a gold standard obtained from manual segmentation using the Dice index, average surface distance (ASD), and Mahalanobis distance (MHD) metrics. Qualitative analysis was also performed between the algorithm and the gold standard of 78 teeth. The Dice index average for all pulp segmentation (n = 78) was 83.82% (SD = 6.54%). ASD for all pulp segmentation (n = 78) was 0.21 mm (SD = 0.34 mm). Pulp segmentation compared with MHD averages was 0.19 mm (SD = 0.21 mm). The results of teeth segmentation metrics were similar to pulp segmentation metrics. For the total teeth (n = 78) included in this study, the Dice index average was 92% (SD = 13.10%), ASD was low at 0.19 mm (SD = 0.15 mm), and MHD was 0.11 mm (SD = 0.09 mm). Despite good quantitative results, the qualitative analysis yielded fair results due to large categories. When compared with existing automatic segmentation methods, our approach enables an effective segmentation for both pulp and teeth. Conclusions Our proposed algorithm for pulp and teeth segmentation yields results that are comparable to those obtained by the state-of-the-art methods in both quantitative and qualitative analysis, thus offering interesting perspectives in many clinical fields of dentistry.

Mandibular Teeth as Predictors in Forensic Age Estimation: A Cone-Beam Computed Tomography-Based Pulp Volume Regression Study

Background

Age estimation is integral to science of forensic odontology and plays an important role in human identification. Pulp volume estimation using cone-beam computed tomography (CBCT) to derive age can be very useful as it is noninvasive and can be applied on individuals of all ages.

Aims and Objectives

The study aimed to estimate the chronological age-based pulp and tooth volume (PTV) ratios in adults from Uttar Pradesh, India, using CBCT and voxel counting dental software.

Materials and Methods

Thirty-six CBCT scans were allocated into three Groups, I, II, and III (12 in each group) randomly to study the pulp volume of lateral incisor, canine, and first premolar, respectively. PTV was calculated by image segmentation method using Xelis Dental software. A correlation between chronological age with PTV was established using derived regression equations.

Statistical Analysis

All the data were subjected to statistical analysis using Statistical Package for Social Sciences version 16.0.

Results

Estimated age and standard error were determined. Standard errors of estimates were 11.24 years (LI), 7.78 years (C), 9.89 years (PM) group, lowest being for canines. The estimated age was compared with the chronological age. The difference between the chronological age and the estimated age by the derived equation for the present study was statistically nonsignificant (P = 1.00).

Conclusions

The results of the study show the feasibility of calculation of PTV ratios on CBCT to estimate the age for the set population with canine as the best predictor of age for the present study population.

3D segmentation of dental crown for volumetric age estimation with CBCT imaging

In adult dental age estimation, segmentation of dental volumetric information from different tooth parts using cone-beam computed tomography (CBCT) has proven beneficial in improving the regression model reliability. This segmentation method can be expanded in the crown part since the volumetric information in the crown is affected by attrition in the enamel and secondary dentine in the dentine and pulp chamber. CBCT scans from 99 patients aged between 20 and 60 were collected retrospectively. A total of 80 eligible teeth for each tooth type were used in this study. The enamel to dentine volume ratio (EDVR), pulp to dentine volume ratio (PDVR) and sex were used as independent variables to predict chronological age (CA). The EDVR was not affected by PDVR. The highest R² was calculated from the maxillary canine (R² = 0.6). The current approach in crown segmentation has proven to improve model performance in anterior maxillary teeth.

Age Estimation Using Maxillary Central Incisor Analysis on Cone Beam Computed Tomography Human Images

Forensic dentistry plays an important role in human identification, and dental age estimation is an important part of the process. Secondary dentin deposition throughout an individual's lifetime and consequent modification in teeth anatomy is an important parameter for age estimation procedures. The aim of the present study was to develop regression equations to determine age in adults by means of linear measurements and ratios on sagittal, coronal and axial slices of maxillary central incisors using cone bean computed tomography (CBCT). Multiplanar measurements of upper central incisors were taken for a sample of 373 CBCTs. Subsequently, one-way analysis of variance (ANOVA) and multivariate linear regressions were performed for age estimation. The equations obtained from axial linear measurements and ratios presented a standard error of the estimate (SEE) of ±10.9 years (R² = 0.49), and a SEE of ±10.8 years (R² = 0.50), respectively. The equation obtained for multiplanar linear measurements presented a SEE of ±10.9 years (R² = 0.52), while the equation for multiplanar ratios presented a SEE of ±10.7 years (R² = 0.51). Thus, CBCT measurements on upper central incisors were found to be an acceptable method for age estimation. Horizontal measurements, especially pulp measurements, improve the accuracy of age estimate equations.

Application of the ratio of the radiopaque calcified area to the dental follicle (RCA/DF) for dental age assessment on orthopantomograms

OBJECTIVES

This study aimed at exploring a new tooth development evaluation method for age assessment and investigating the dynamic alteration and potential trend of tooth development by orthopantomograms (OPGs), in order to provide references for tooth development prediction and forensic purpose.

MATERIALS AND METHODS

A total of 132 OPGs of children aged 3-8 years were collected. The developmental stages of the permanent mandibular second molar (M2)were evaluated by experienced examiners according to the Nolla method and Mimics software, respectively. Quantitative analysis of the ratio of the radiopaque calcified area to the dental follicle (RCA/DF) in different stages, ages, sexes and quadrants were evaluated and compared via descriptive statistics and Spearman's correlation coefficient analysis.

RESULTS

There was a strong, positive correlation between the examiners' evaluation and mimics analysis results. With the age increased, the Nolla stage of M2 observed by OPGs increased, and the RCA/DF showed increased trends both in males and females. There were significant differences of the RCA/DF of the M2 at various ages. The tooth calcification development of female was 9.08% earlier than that of male between 3 and 8 years old. However, teeth of male seemed to develop faster than that of female during this period. There was no significant difference between left and right quadrant either according to the Nolla stage or RCA/DF.

CONCLUSIONS

The RCA/DF value obtained from OPGs of the developmental mandibular second permanent molars could be used as a reliable indicator for tooth maturity and age estimation in children aged 3-8 years.

CLINICAL RELEVANCE

Age assessment based on radiographs is considered as a reliable and efficient indicator for judging different types of malocclusion, making suitable orthodontic treatment plan, deciding the extraction time of retained deciduous teeth in clinic practice.

Age estimation in young dogs by radiographic assessment of the canine pulp cavity/tooth width ratio

Age estimation in adult dogs can be performed by the radiographic measurement of the tooth pulp cavity, but the technique has hardly been described. In this study, the application of measuring pulp/tooth width ratios (P/T ratios) of the maxillary canine teeth was investigated. Pulp and tooth widths were measured at two locations on 166 maxillary canine teeth of the heads of 84 dog cadavers, using digital extraoral lateral oblique open mouth radiographs. The dogs belonged to different breeds and sexes and had a known age between 194 and 1907 days (approximately 6 months - 5 years). Both at the cemento-enamel junction (CE) and the half-height of the tooth, a comparable non-linear regression with age was demonstrated. Measuring at the CE location was less hindered by wear or superimposition. No statistically significant difference according to sex and breed size and no clinically significant difference according to skull type was found. The highest predictable capacity was found in the youngest dogs until the age of 448 days, of which 84.4% of the canine teeth had a P/T ratio above 0.39. Our results demonstrate that measuring P/T ratios of canine teeth can be used in practice to assign dogs to age categories, with the highest accuracy in young adult dogs.

Population-specific age estimation in Black Americans and Chinese people based on pulp chamber volume of first molars from cone beam computed tomography

OBJECTIVES

To validate the fitness of the age estimation model in Black Americans, which was previously and solely established for the Chinese population based on pulp chamber volume of the first molars from cone beam computed tomography (CBCT), and to establish a new age estimation model for Black Americans.

MATERIALS AND METHODS

A total of 203 subjects with CBCT scans, including 119 Chinese and 84 Black Americans, were retrospectively identified. The age range of subjects was between 11 and 87 years. For both populations, automated 3D pulp chamber segmentation of the first molars was performed by deep learning, followed by volume calculation and age estimation by a logarithmic regression model, which was established in a prior study solely on Chinese population. Additionally, a separate logarithmic regression analysis was carried out on Black Americans. The performance of age estimation was assessed by the mean absolute error (MAE), root mean square error (RMSE), Wilcoxon signed rank test, and coefficient of determination (R²) between the actual and estimated human ages.

RESULTS

When applying the age estimation model established in the prior study, MAE = 7.994 years and RMSE = 10.065 years were observed in the Chinese population, while MAE = 14.049 years and RMSE = 17.866 years were observed in Black Americans. The new age estimation model established for Black Americans was AGE = 89.752 - 21.176 × lnV (V = pulp chamber volume), with MAE = 7.930 years, RMSE = 10.664 years, and coefficient of determination (R²) = 0.600.

CONCLUSIONS

Population-specific age estimation is needed when applied in Black Americans and Chinese people based on pulp chamber volume of the first molars from CBCT.

CBCT in dental age estimation: A systematic review and meta analysis

OBJECTIVES

This study aimed to investigate the reproducibility of dental age estimation methods in cone beam computed tomography (CBCT) and the correlation between dental (DA) and chronological (CA) ages.

METHODS

The scientific literature was searched in six databases (PubMed, Scopus, LILACS, Web of Science, SciELO, and OATD). Only observational studies were selected. Within each study, the outcomes of interest were (I) the quantified reproducibility of the method (κ statistics and Intraclass correlation coefficient); and (II) the correlation (r) between the dental and chronological ages. A random-effect three-level meta-analysis was conducted alongside moderator analysis based on methods, arch (maxillary/mandibular), population, and number of roots.

RESULTS

From 671 studies, 39 fulfilled the inclusion criteria, with one study reporting two different methods. The methods used in the studies were divided into metric (n = 17), volumetric (n = 20), staging (n = 2), and atlas (n = 1). All studies reported high examiner reproducibility. Group 1 (metric and volumetric) provided a high inverse weighted r ([Formula: see text] = -0.71, CI [-0.79,-0.61]), and Group 2 (staging) provided a medium-weighted r ([Formula: see text] = 0.49, CI [0.44, 0.53]). Moderator analysis on Group one did not show statistically significant differences between methods, tooth position, arch, and number of roots. An exception was detected in the analysis based on population (Southeast Asia, [Formula: see text] = -0.89, CI [-0.94,-0.81]).

CONCLUSION

There is high evidence that CBCT methods are reproducible and reliable in dental age estimation. Quantitative metric and volumetric analysis demonstrated better performance in predicting chronological age than staging. Future studies exploring population-specific variability for age estimation with metric and volumetric CBCT analysis may prove beneficial.

Age Estimation Based on Pulp–Tooth Volume Ratio of Anterior Teeth in Cone-Beam Computed Tomographic Images in a Selected Population: A Cross-Sectional Study

The present study aimed to investigate the correlation between chronological age and pulp–tooth volume ratio in anterior teeth using cone beam computed tomographic (CBCT) images and provide equations for age estimation based on pulp–tooth volume ratio. In this cross-sectional study, CBCT images of 312 anterior teeth of the maxilla and mandible were examineαd. The chronological age and the sex of the patients were recorded. Tooth volume and pulp volume of the anterior teeth were measured using Mimics software, and then tooth–pulp volume ratio was calculated. Statistical analysis of data was performed using chi-square test, independent T-test, Pearson’s correlation, and linear regression (α = 0.05). Finally, equations were made based on the results of the regression analysis for age estimation in general and for males and females. The age of the subjects ranged between 16 and 69 years (mean 40.6 ± 12.74). The pulp–tooth volume ratio of the maxillary teeth was generally higher than the mandibular teeth. A significant inverse relationship between age and pulp–tooth volume ratio was observed for all anterior teeth. (p < 0.05). The strongest correlation between age and pulp–tooth volume ratio was reported for mandibular central incisor (r = −0.58, p < 0.001) and the weakest was for mandibular lateral incisor (r = −0.36, p = 0.012). Age estimation was most accurate among females using the maxillary central incisors (p < 0.001) and among males using the mandibular central incisors and maxillary canines (p = 0.003). Pulp–tooth volume ratio of mandibular central incisors, maxillary lateral incisors, and maxillary canines in males and maxillary and mandibular central incisors, maxillary lateral incisors, and maxillary and mandibular canines in females can be used for age estimation.

Zur Anwendbarkeit der dentalen Methode von Roberts et al. aus dem Jahr 2016 zum Nachweis der Vollendung des 18. Lebensjahres lebender Personen

Es sollte die Methode von Roberts et al. aus dem Jahr 2016 zum Nachweis der Vollendung des 18. Lebensjahres überprüft werden.

Dazu wurden 603 Orthopantomogramme (OPG) von 300 Frauen und 303 Männern im Alter von 16,01 bis 25,99 Jahren von 3 Untersuchern ausgewertet, wobei ein Hauptuntersucher alle OPGs zweimal begutachtet hat. Durch die 3 Untersucher wurde eine konsensuale Bestimmung für die Fälle vorgenommen, bei denen mindestens ein Untersucher ein Stadium zugeordnet hatte.

In 31 Fällen (11 Frauen, 20 Männer) konnte konsensuell ein Stadium bestimmt werden. Hauptursache für die Nichtauswertbarkeit war die nicht abgeschlossene Entwicklung des Zahnes 38 [FDI] (30,18 %), gefolgt von Karies, Restaurationen oder anderen Pathologien (20,56 %) und dem Fehlen des Zahnes 38 (19,57 %). Das Stadium „RCW‑C“ konnte bei den Frauen konsensual nicht, die Stadien „RCW‑B“ und „RCW‑C“ konnten bei den Männern nur 4‑mal (3x „RCW-C“, 1x „RCW-B“) bestimmt werden. Der Cohen’s-Kappa-Wert für die Binnenbeobachterübereinstimmung für die 47 Fälle, in denen der Hauptuntersucher in mindestens einem Durchgang ein Stadium zugeordnet hatte, lag im moderaten bzw. guten Bereich (Frauen: 0,44; Männer: 0,62). Der Fleiss’-Kappa-Wert für die Zwischenbeobachterübereinstimmung der 3 Untersucher für die 69 Fälle, bei denen mindestens ein Untersucher ein Stadium zugeordnet hatte, lag im mangelhaften Bereich (Frauen: 0,07; Männer: 0,11), wobei die 95%-Konfidenzintervalle für den Kappa-Wert auch die „0“ einschlossen.

Alle Personen, bei denen ein Stadium zugeordnet wurde, waren über 18 Jahre alt. Aktuell kann eine Anwendung der Methode nicht empfohlen werden. Es wird die Frage aufgeworfen, ob den Stadien eine allgemeingültige Entwicklungsabfolge zu Grunde zu liegt, da bei 30 Fällen der Befund nicht mit den Stadien in Deckung zu bringen war.

Tooth and Bone Parameters in the Assessment of the Chronological Age of Children and Adolescents Using Neural Modelling Methods

The analog methods used in the clinical assessment of the patient's chronological age are subjective and characterized by low accuracy. When using those methods, there is a noticeable discrepancy between the chronological age and the age estimated based on relevant scientific studies. Innovations in the field of information technology are increasingly used in medicine, with particular emphasis on artificial intelligence methods. The paper presents research aimed at developing a new, effective methodology for the assessment of the chronological age using modern IT methods. In this paper, a study was conducted to determine the features of pantomographic images that support the determination of metric age, and neural models were produced to support the process of identifying the age of children and adolescents. The whole conducted work was a new methodology of metric age assessment. The result of the conducted study is a set of 21 original indicators necessary for the assessment of the chronological age with the use of computer image analysis and neural modelling, as well as three non-linear models of radial basis function networks (RBF), whose accuracy ranges from 96 to 99%. The result of the research are three neural models that determine the chronological age.

Accurate age classification using manual method and deep convolutional neural network based on orthopantomogram images

Age estimation is an important challenge in many fields, including immigrant identification, legal requirements, and clinical treatments. Deep learning techniques have been applied for age estimation recently but lacking performance comparison between manual and machine learning methods based on a large sample of dental orthopantomograms (OPGs). In total, we collected 10,257 orthopantomograms for the study. We derived logistic regression linear models for each legal age threshold (14, 16, and 18 years old) for manual method and developed the end-to-end convolutional neural network (CNN) which classified the dental age directly to compare with the manual method. Both methods are based on left mandibular eight permanent teeth or the third molar separately. Our results show that compared with the manual methods (92.5%, 91.3%, and 91.8% for age thresholds of 14, 16, and 18, respectively), the end-to-end CNN models perform better (95.9%, 95.4%, and 92.3% for age thresholds of 14, 16, and 18, respectively). This work proves that CNN models can surpass humans in age classification, and the features extracted by machines may be different from that defined by human.