Home About us Editorial board Search Ahead of print Current issue Archives Submit article Instructions Subscribe Contacts Login 
    Users Online: 108
Home Print this page Email this page Small font size Default font size Increase font size


 
 Table of Contents  
ORIGINAL ARTICLE
Year : 2022  |  Volume : 11  |  Issue : 3  |  Page : 190-196

Dental pattern diversity in a Saudi Arabian population: An orthopantomogram-based study


Departments of Orthodontics and Pediatric Dentistry, College of Dentistry, Qassim University, Buraidah, Saudi Arabia

Date of Submission25-Aug-2022
Date of Decision06-Oct-2022
Date of Acceptance10-Oct-2022
Date of Web Publication30-Nov-2022

Correspondence Address:
Nabeel Almotairy
Al-Mulida, Prince Nayef bin Abdulaziz street, Buraidah 52571
Saudi Arabia
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/sjhs.sjhs_93_22

Rights and Permissions
  Abstract 


Background: Dental pattern diversity was investigated in different populations, but none have focused on Saudi Arabia. Aim: The aim of this study was to investigate the dental pattern diversity in Saudi Arabia. Setting and Design: This was a retrospective study. Materials and Methods: Five thousand two hundred and twenty-five orthopantomograms of healthy dentate adults were divided into four age groups: Group 1, 18–30 years; Group 2, 31–45 years; Group 3, 46–55 years; and Group 4, >55 years. The conditions of the 32 teeth in each individual were assigned to 10 characteristics to form a dental pattern, and the diversity of patterns was estimated using the Simpson's Diversity Index. Statistical Analysis: The diversity, proportions, and frequency of unique dental patterns were descriptively compared between age groups and sexes. Results: The dental pattern diversity for full dentition was >0.99, with 5024 unique dental patterns. The diversity and frequency of dental patterns were lower in the maxillary and mandibular anterior segments compared to those in posterior segments. All virgin teeth were the most frequently observed dental pattern for full dentition (1.24%). The dental pattern diversity for full dentition was similar across the age groups, but the frequency of unique dental patterns was 68.23%, 91.47%, 90.39%, and 88.89% for Groups 1, 2, 3, and 4, respectively. Further, the frequency of unique dental patterns was 10%–20% higher in females than in males. Conclusions: The dental pattern diversity was high in the studied Saudi Arabian sample and was affected by individuals' age and sex, where older individuals and females have higher diversity than younger individuals and males.

Keywords: Dental bioinformatics, dental identification, forensic dentistry, forensic odontology, human identification, panoramic radiograph


How to cite this article:
Almotairy N, Althunayyan A, Alkhuzayyim D, Aloufi L, Alhusayni R. Dental pattern diversity in a Saudi Arabian population: An orthopantomogram-based study. Saudi J Health Sci 2022;11:190-6

How to cite this URL:
Almotairy N, Althunayyan A, Alkhuzayyim D, Aloufi L, Alhusayni R. Dental pattern diversity in a Saudi Arabian population: An orthopantomogram-based study. Saudi J Health Sci [serial online] 2022 [cited 2023 Jan 28];11:190-6. Available from: https://www.saudijhealthsci.org/text.asp?2022/11/3/190/362383




  Introduction Top


Natural catastrophes often lead to mass fatalities, as was evidenced in the 2011 East Japan earthquake and tsunami. It was a catastrophic event in which the tsunami's expansive destructive impact on the coastline resulted in the need for victim identification. The victim identification report of this catastrophe showed that dental records have significantly contributed to efficient victim identification compared to other biometric methods, such as fingerprint or DNA-based methods.[1]

In incidences such as mass deaths, human identification is a grueling and complicated process, with DNA-based human identification being regarded as an advanced and precise method. On the other hand, to execute DNA analysis, certain laboratory facilities are necessary along with adequate DNA samples that must be properly preserved.[2] In contrast, teeth are hard structures, and regardless of the body state, they are often preserved, making them valuable and reliable tools in human identification after catastrophic incidents.[3],[4],[5],[6],[7],[6] Hence, using teeth for human identification is regarded as a sensitive and quick method.[7]

Forensics uses human dentition in a number of ways, including for assessing tooth bite marks or radiographic crown and root development.[8],[9] Previous studies have employed the distinct morphological characteristics (relative position, restoration shape, and contour) of the tooth that can be seen under dental radiography.[10],[11],[12],[13] Some studies have also used orthopantomography (OPG) to examine the differences in tooth patterns and characteristics in individuals.[4],[14],[15],[16] Dental patterns have been used since 66 A. D., and progress in dental investigative methods including dental casts, treatment history notes, and photographic and radiographic records resulted in dental patterns being used in ante- and postmortem personal identification.[4],[17]

OPG is a typical example of a radiographic record routinely acquired in dental visits. The first use of OPG in personal forensic identification was made by Gösta Gustafson in 1947.[18] The availability of OPGs made them valuable records in comparing ante- and postmortem dental characteristics. The holistic orofacial view provided by OPGs offers great advantages in preserving the dental and jaw status records, thus providing a practical and cost-effective method in identifying victims of catastrophic disasters.

Dental pattern comparison involves distinct dental features including how the teeth are shaped, dental restorations, fixed prostheses, crowns, as well as missing, supernumerary, and impacted teeth. The human mouth has 32 teeth and thus involves a number of combinations of dental patterns which also allows the quantification of the identification process.[4],[16] Hence, if dental pattern frequency is empirically observed from a large and representative sample, it can help in assessing a population's dental pattern diversity more accurately. Studies have examined differences in dental patterns in numerous nationalities suggesting the importance of further studies to focus on other nationalities.[14],[15],[16],[19],[20],[21],[22],[23] It should be noted that no studies have examined the diversity of dental pattern characteristics in Saudi Arabia. Therefore, the present study aims to use OPG radiographs to assess dental pattern diversity in a Saudi Arabian population as well as determine how age and sex impact dental pattern diversity.


  Materials and Methods Top


The study was approved by the Committee of Research Ethics at Qassim University, Saudi Arabia (#21-01-06). Based on a similar study,[15] the present study needed a sample size of 5000 OPGs. The radiographs were retrospectively acquired from the College of Dentistry database. These radiographs were of Saudi Arabian individuals who are 18 years or older, were of good quality, and showed no pathological anomalies such as tumors, cysts, and cleft lip and palate. Radiographs of patients who have deciduous teeth or are entirely edentulous were excluded.

All collected OPGs were obtained using CRANEX D Digital Panoramic and Cephalometric X-ray Unit (SOREDEX™, Tuusula, Finland). The sample was divided according to the patient's age into four groups (Group 1 = 18–30 years, Group 2 = 31–45 years, Group 3 = 46–55 years, and Group 4 ≥55 years). The maxillary and mandibular dental arches were divided into three segments (anterior, posterior right, and posterior left). Using Microsoft Excel, the state of every single tooth at each maxillary and mandibular segment was coded into ten codes, as shown in [Table 1]. The collective tooth codes for the full dentition and in each maxillary and mandibular segment were combined to form a dental pattern for each individual OPG, as exemplified in [Figure 1].
Table 1: Tooth characteristics applied in this study

Click here to view
Figure 1: An example of the coding method for each individual tooth at each of the three maxillary and mandibular segments

Click here to view


The diversity of dental patterns across the Saudi Arabian population was estimated using the Simpson's Diversity Index (SDI):



where n is the total number of individuals in each unique dental pattern and N is the total number of the sample. A diversity value between 0 and 1 was obtained. A value closer to 1 indicates an increased diversity in a population and a value closer to 0 indicates a decreased diversity in a population.

Method error

Four trained dentists worked together to calibrate and assign the codes of a random sample of 50 OPGs that were not included in the sample during two sessions, 2 weeks apart. The inter-rater agreement in assigning the codes between the four dentists was assessed using the intraclass correlation coefficient (two-way mixed model with absolute agreement). The results showed good inter-rater agreement (0.793, 95% confidence interval [0.722–0.845], P < 0.0001). All dentists were given a 1-week washout period before they began coding all the collected OPGs over the subsequent 8 weeks.

Statistics

The descriptive data related to the patient's age and gender were calculated, and the collective code pattern for each OPG was recorded in an Excel sheet. Microsoft Excel's Pivot Tables were used to calculate the proportion of the unique dental patterns in the maxillary and mandibular segments and full dentition. The frequency of unique dental patterns in relation to dentition, age, and gender was calculated by dividing the number of obtained unique patterns by the number of individuals in each category. Age- and sex-related changes in the collected variables (SDI, dental pattern proportion, and frequency) were also descriptively presented.


  Results Top


Sample characteristics

The collected sample included 5225 OPGs of individuals with an average age of 40 ± 14.1 years (24.1% of females). All the radiographs were taken during the last 4 years (2018–2021). [Table 2] shows the detailed sample demographics of the different age groups.
Table 2: Study sample demographics

Click here to view


Overall dental pattern diversity

The overall dental pattern diversity for the full dentition was 1, with 5024 unique dental patterns [Table 3]. The SDI for both the maxillary and mandibular teeth was also 1 with 4297 and 4175 unique dental patterns, respectively, for both arches. Similar dental pattern diversity was shown in the maxillary and mandibular segments (0.98), except for the maxillary and mandibular anterior teeth where the dental patterns were 0.8 and 0.53, respectively [Table 3]. The most frequent dental pattern for full dentition was all virgin teeth [1.24%], followed by all virgin teeth with a missing maxillary right third molar (0.17%). The most frequent dental pattern across the maxillary and mandibular segments was also virgin teeth, ranging between 9% and 13% for posterior right and left segments, while it was 44.5% and 68.3% for the maxillary and mandibular front tooth segment, respectively. Moreover, the right and left maxillary and mandibular segments had a similar number of unique dental patterns [Table 3] and [Figure 2]. However, the number of unique dental patterns in the mandibular anterior segment was one-third of what was observed in the maxillary anterior segment. The overall frequency of unique dental patterns for full dentition was 96.15% [Figure 2]. The number and frequency of the five most frequent dental patterns in the maxillary and mandibular segments and full dentition across the four age groups.
Table 3: The age- and sex-related changes in the number of unique dental patterns and Simpson's Diversity Index for the maxillary and mandibular right, front, and left teeth and full dentition

Click here to view
Figure 2: The frequency of unique dental patterns in the maxillary and mandibular segments and full dentition across the age groups

Click here to view


Age-related changes in dental pattern diversity

The four age groups showed similar dental pattern diversity of the full dentition [Table 3]. Moreover, the dental pattern diversity of the whole maxillary and mandibular teeth showed no age-related changes. All age groups also showed similar dental pattern diversity in the posterior right and left segments of both maxillary and mandibular teeth, except Group 1 which had lower diversity in the maxillary posterior segments. The dental pattern diversity of both the maxillary and mandibular front teeth was also the lowest in Group 1, which peaked in Group 2 and slightly reduced in Groups 3 and 4. The number of unique dental patterns for the full dentition was the lowest in Group 4, followed by Group 3, and peaking in Group 2 [Table 3]. The most frequent dental pattern for full dentition was all virgin teeth for Groups 1–4 (3.16%, 0.67%, 0.49%, and 0.37%, respectively). All virgin teeth dental pattern was also the most frequent dental pattern in the maxillary and mandibular segments in Groups 1–3 and declined with age. All virgin teeth dental pattern was the most frequent in Group 4 in the whole maxillary and mandibular teeth and anterior segment for both arches but not in the posterior right and left segments. All missing teeth were the most frequent dental pattern in the left maxillary posterior segment and the right and left mandibular posterior segments in Group 4 (4.95%, 5.14%, and 4.67%, respectively). The frequency of unique dental patterns was 93.48%, 98.87%, 98.62%, and 96.45% for Groups 1, 2, 3, and 4, respectively [Figure 2]. The number and frequency of the five most frequent dental patterns in the maxillary and mandibular segments and full dentition in the four age groups.

Sex-related changes in dental pattern diversity

Although the number of unique dental patterns was higher in males than females across the different age groups, no sex-related changes were observed in the diversity of dental patterns [Table 3]. The most frequent dental pattern in the maxillary and mandibular segments was all virgin teeth for both sexes in Groups 1 and 2. In Group 3, the most frequent dental pattern in males was all virgin teeth in the maxillary and mandibular segments, but this was not the case for females. In Group 4, both the sexes showed all virgin teeth in the maxillary and mandibular anterior segments and all missing teeth in the mandibular right and left posterior segments. In Groups 1 and 2, for both sexes, the most frequent dental pattern for full dentition was all virgin teeth. For Groups 3 and 4, all virgin teeth dental pattern was the most frequent for males but not females. The frequency of unique dental patterns in the maxillary and mandibular posterior segments was approximately 10% lower for males than females in all groups except Group 1 where it was 20% lower than females [Figure 3]. The frequency of unique dental patterns for full dentition was 90% for both males and females [Figure 3]. The number and frequency of the five most frequent dental patterns in the maxillary and mandibular segments and full dentition between the sexes in the four age groups.
Figure 3: The frequency of unique dental patterns in the maxillary and mandibular segments and full dentition between the sexes across the age groups

Click here to view



  Discussion Top


The present study investigated the dental pattern diversity and the effects of age and sex using OPG radiographs in a Saudi Arabian population. Before conducting the current study, the common tooth characteristics used to form the dental pattern were determined. Thus, ten tooth characteristics were identified to diversify the sample and minimize the number of individuals in the sample with identical patterns. Yılancı et al.[22] investigated the effect of the number of included tooth characteristics on the diversity of dental pattern using 169 OPGs. They concluded that dental diversity was low when only four tooth characteristics were used, but higher dental pattern diversity was observed when there were 6 or 11 characteristics. Sheets et al.[24] also commented that small sample size can influence the outcome of tooth uniqueness analysis. This may indicate that the increase in the number of tooth characteristics necessitates an increase in the investigated sample size. Therefore, this study implemented 10 tooth characteristics using more than 5000 OPGs to avoid misleading outcomes.

The current study also showed that the diversity and frequency of unique dental patterns for the entire sample were lower in the maxillary and mandibular segments (anterior, posterior right, and posterior left) than full dentition. This can be explained by the limited number of teeth in the maxillary and mandibular segments compared to full dentition, thus limiting the diversity of unique dental patterns. Moreover, the diversity and frequency of unique dental patterns for the entire sample were lower in the maxillary and mandibular anterior segments than in posterior segments, reflecting a higher incidence of dental diseases in posterior than anterior teeth.[16]

In this study, the overall dental pattern diversity was more than 0.99, corroborating previous studies of other nationalities.[4],[14],[16],[19],[20],[21],[22],[23],[25],[26] The human dentition comprises 32 teeth, and as the present study used 10 possible codes, it allowed the distinction of 5024 unique dental patterns in 5225 individuals. The high frequency of unique dental patterns could imply that human dental pattern is a feasible and objective method for individual identification.[4] For example, the probability of finding a person with bilaterally impacted third molars in the maxillary and mandibular teeth with the entire rest of teeth being sound (virgin) is very close to zero (0.04%) for the studied sample. It indicates that the chance of randomly selecting two individuals with the same dental pattern is very slim.

The increased access to free oral health-care services in Saudi Arabia and the adoption of oral prevention programs may have led to better teeth maintenance.[27] In this regard, the current study showed that the most frequent dental pattern for full dentition in the studied sample was all virgin teeth (1.24%). All virgin teeth were also the most frequent dental pattern observed in Indians and Peruvians, whereas the most frequent dental pattern in South Korean and Turkish populations was impacted third molars with the remaining teeth all virgin.[14],[19],[20],[21],[22] The ethnic-related differences could explain the variation of the most frequent dental pattern observed across different populations. Indeed, studies have shown that tooth development and eruption can be influenced by several factors such as genetic, sexual, nutrition, and racial variations.[28] Other factors such as the country's economic circumstances, individual lifestyle and living situation, and dental care accessibility and people's perception of it can also lead to variations in dental pattern diversity across different populations.[29],[30],[31]

Dental pattern diversity is known to be dependent on population age and the extent of dental caries.[16],[23] The current study showed that the frequency of dental patterns was lowest in Group 1 and increased in Groups 2–4. This indicates that dental pattern diversity increases with age because of the increased probability of dental treatments.[23] The current study also showed that all virgin teeth dental pattern was the most frequently observed dental pattern in the maxillary and mandibular segments in Groups 1–3, but the most frequently observed dental pattern in Group 4 was all missing teeth in the left maxillary posterior segment and the bilateral posterior mandibular segments. In recent times, the proportion of older adults increased along with an increase in their dental care demand.[31],[32] Previous studies have shown that older adults have a higher risk of periodontal and oral diseases and have more active dental caries than young adults.[33],[34],[35] Older adults are also less likely to seek dental care, with many only seeking treatment after they feel pain.[34] Therefore, these factors may lead to more susceptibility to tooth loss in older adults than younger adults.[35]

In this study, more males were included than females, resulting in an increased number of unique dental patterns observed in the former than the latter. Interestingly, the frequency of unique dental patterns was 10%–20% higher in females than in males [Figure 3]. This can probably be explained by the sex-related differences in oral hygiene habits and perception of dental care.[36] Studies have shown that males are more likely to exhibit low oral hygiene awareness, inadequate oral hygiene maintenance, and have more oral diseases than females.[36] Males also seek dental treatment less frequently than females and are more likely to seek treatment for painful problems than disease prevention. On the other hand, females exhibited more positive oral hygiene awareness and practices and sought dental therapies more often than males.[36] Nevertheless, the inequal sample between the sexes in this study may have negated any differences in dental pattern diversity. Thus, future studies should include more females to help detect any sex-related differences in dental pattern diversity.

Limitations

A major drawback of using dental pattern diversity to identify individuals is the requirement of good-quality antemortem OPG data.[16],[37] These records must be updated by taking into consideration dental aging or treatment changes. There are also other limitations such as no regional data for comparison and data missing from various age groups that this study has not included. Moreover, a standardization protocol is required for dental pattern diversity so that the dental data can be interpreted and assessed across international forensic dentists.[38] The present study observed that age and dental interventions increase the diversity of dental patterns, thus suggesting that improved national oral health awareness can reduce dental diversity, which can restrict the effectiveness of individual identification. In such cases, other supplementary oral features including maxillofacial anomalies and tooth morphological characteristics can be employed for individuals who have low dental pattern diversity.[11],[12],[13],[39],[40] While using OPG for tooth characteristic identification is an easy method, it can be time-consuming and laborious. In the present study, four experienced dentists assessed 5225 radiographs in 8 weeks. Recent studies, however, have examined the relevancy of artificial intelligence and deep learning in tooth radiographic recognition.[11],[41],[42] Employing such methods can help automate dental pattern recognition in a wider population database which can enhance its adaptability in personal identification, like fingerprints. It is recommended that future studies investigate computer-aided technology in terms of tooth characteristic recognition and how it can be used to examine dental pattern diversity.


  Conclusions Top


In this study, it was observed that the dental pattern diversity was high in the Saudi Arabian sample. The age and sex of individuals affected dental pattern diversity, with older individuals and females having high diversity than younger individuals and males.

Data availability statement

The datasets generated during and/or analyzed during the current study are available in the supplementary and can be accessed through the link https://osf.io/u6hae/.

Acknowledgments

The authors gratefully acknowledge Qassim University, represented by the Deanship of Scientific Research, on the financial support for this research under the number (20014-dent-2021-1-2-w) during the academic year 1443 AH/2022 AD.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Aoki T, Ito K, Aoyama S, Kosuge E. Disaster victim identification using dental records – Experience of the Great East Japan Earthquake. In: 2013 IEEE Region 10 Humanitarian Technology Conference IEEE; 2013. p. 57-62.  Back to cited text no. 1
    
2.
Budowle B, Bieber FR, Eisenberg AJ. Forensic aspects of mass disasters: Strategic considerations for DNA-based human identification. Leg Med (Tokyo) 2005;7:230-43.  Back to cited text no. 2
    
3.
Gutiérrez-Salazar MP, Reyes-Gasga J. Microhardness and chemical composition of human tooth. Mater Res 2003;6:367-73.  Back to cited text no. 3
    
4.
Adams BJ. The diversity of adult dental patterns in the United States and the implications for personal identification. J Forensic Sci 2003;48:497-503.  Back to cited text no. 4
    
5.
Nambiar P, Jalil N, Singh B. The dental identification of victims of an aircraft accident in Malaysia. Int Dent J 1997;47:9-15.  Back to cited text no. 5
    
6.
Petju M, Suteerayongprasert A, Thongpud R, Hassiri K. Importance of dental records for victim identification following the Indian Ocean tsunami disaster in Thailand. Public Health 2007;121:251-7.  Back to cited text no. 6
    
7.
Wood RE. Forensic aspects of maxillofacial radiology. Forensic Sci Int 2006;159 Suppl 1:S47-55.  Back to cited text no. 7
    
8.
DeVore DT. Bite marks for identification? A preliminary report. Med Sci Law 1971;11:144-5.  Back to cited text no. 8
    
9.
Cummaudo M, De Angelis D, Magli F, Minà G, Merelli V, Cattaneo C. Age estimation in the living: A scoping review of population data for skeletal and dental methods. Forensic Sci Int 2021;320:110689.  Back to cited text no. 9
    
10.
Jain AK, Chen H. Matching of dental X-ray images for human identification. Pattern Recognit 2004;37:1519-32.  Back to cited text no. 10
    
11.
Nomir O, Abdel-Mottaleb M. A system for human identification from X-ray dental radiographs. Pattern Recognit 2005;38:1295-305.  Back to cited text no. 11
    
12.
Nomir O, Abdel-Mottaleb M. Human identification from dental X-ray images based on the shape and appearance of the teeth. IEEE Trans Inf Forensics Secur 2007;2:188-97.  Back to cited text no. 12
    
13.
Franco A, Willems G, Souza PH, Bekkering GE, Thevissen P. The uniqueness of the human dentition as forensic evidence: A systematic review on the technological methodology. Int J Legal Med 2015;129:1277-83.  Back to cited text no. 13
    
14.
Lee SS, Choi JH, Yoon CL, Kim CY, Shin KJ. The diversity of dental patterns in the orthopantomography and its significance in human identification. J Forensic Sci 2004;49:784-6.  Back to cited text no. 14
    
15.
Guimarães MI, Martínez Chicón J, Gonçalves J, Carneiro Sousa MJ, Márquez Ruiz AB, Valenzuela Garach A. Diversity in dental clinical characteristics in Portuguese and Spanish military populations. Rev Española Med Leg 2018;44:99-107.  Back to cited text no. 15
    
16.
Biazevic MG, de Almeida NH, Crosato E, Michel-Crosato E. Diversity of dental patterns: Application on different ages using the Brazilian National Oral Health Survey. Forensic Sci Int 2011;207:240.e1-9.  Back to cited text no. 16
    
17.
Stavrianos C, Kokkas A, Andreopoul E, Eliades A. Applications of forensic dentistry: Part-I. Res J Med Sci 2010;4:179-86.  Back to cited text no. 17
    
18.
Gustafson G. Age determinations of teeth. Odontol Tidskr 1947;55:556-68.  Back to cited text no. 18
    
19.
Perez IE. Dental patterns in Peruvians: A panoramic radiography study. J Forensic Odontostomatol 2015;33:9-17.  Back to cited text no. 19
    
20.
Kumar A, Ghosh S, Logani A. Occurrence of diversity in dental pattern and their role in identification in Indian population: An orthopantomogram based pilot study. J Forensic Dent Sci 2014;6:42-5.  Back to cited text no. 20
[PUBMED]  [Full text]  
21.
Bhateja S, Arora G, Katote R. Evaluation of adult dental patterns on orthopantomograms and its implication for personal identification: A retrospective observational study. J Forensic Dent Sci 2015;7:14-7.  Back to cited text no. 21
[PUBMED]  [Full text]  
22.
Yılancı HÖ, Akkaya N, Göksülük D. A preliminary study of dental patterns in panoramic radiography for forensic identification. Rom J Leg Med 2017;25:75-81.  Back to cited text no. 22
    
23.
Martin-de-Las-Heras S, Valenzuela A, Luna Jde D, Bravo M. The utility of dental patterns in forensic dentistry. Forensic Sci Int 2010;195:166.e1-5.  Back to cited text no. 23
    
24.
Sheets HD, Bush PJ, Bush MA. Patterns of variation and match rates of the anterior biting dentition: Characteristics of a database of 3D-scanned dentitions. J Forensic Sci 2013;58:60-8.  Back to cited text no. 24
    
25.
Lee C, Lim SH, Huh KH, Han SS, Kim JE, Heo MS, et al. Performance of dental pattern analysis system with treatment chronology on panoramic radiography. Forensic Sci Int 2019;299:229-34.  Back to cited text no. 25
    
26.
Deitos AR, Azevedo AC, Michel-Crosato E, Biazevic MG. Oral health condition of the Brazilian adolescents and its influence on dental diversity patterns for human identification. South Eur J Orthod Dentofac Res 2017;2:35-44.  Back to cited text no. 26
    
27.
Alshahrani AM, Raheel SA. Health-care system and accessibility of dental services in kingdom of Saudi Arabia: An update. J Int Oral Health 2016;8:883-7.  Back to cited text no. 27
  [Full text]  
28.
Seymen F, Folayan MO. Introduction to tooth eruption, tooth emergence and developmental dental hard-tissue anomalies. In: Folayan MO, editor. A Global Compendium of Oral Health Tooth Eruption and Hard Dental Tissue Anomalies 1st ed. United Kingdom: Cambridge Scholars Publishing; 2019. p. 3.  Back to cited text no. 28
    
29.
Osterberg T, Era P, Gause-Nilsson I, Steen B. Dental state and functional capacity in 75-year-olds in three Nordic localities. J Oral Rehabil 1995;22:653-60.  Back to cited text no. 29
    
30.
Hosseinpoor AR, Itani L, Petersen PE. Socio-economic inequality in oral healthcare coverage: Results from the world health survey. J Dent Res 2012;91:275-81.  Back to cited text no. 30
    
31.
Available from: https://www.who.int/news-room/fact-sheets/detail/oral-health. [Last accessed on 2022 Mar 4].  Back to cited text no. 31
    
32.
Kiyak HA. Successful aging: Implications for oral health. J Public Health Dent 2000;60:276-81.  Back to cited text no. 32
    
33.
Chalmers JM. Geriatric oral health issues in Australia. Int Dent J 2001;51:188-99.  Back to cited text no. 33
    
34.
Walls AW, Steele JG. Geriatric oral health issues in the United Kingdom. Int Dent J 2001;51:183-7.  Back to cited text no. 34
    
35.
Müller F, Shimazaki Y, Kahabuka F, Schimmel M. Oral health for an ageing population: The importance of a natural dentition in older adults. Int Dent J 2017;67 Suppl 2:7-13.  Back to cited text no. 35
    
36.
Lipsky MS, Su S, Crespo CJ, Hung M. Men and oral health: A review of sex and gender differences. Am J Mens Health 2021;15:15579883211016361.  Back to cited text no. 36
    
37.
Sweet D. Forensic dental identification. Forensic Sci Int 2010;201:3-4.  Back to cited text no. 37
    
38.
Martínez-Chicón J, Valenzuela A. Usefulness of Forensic Dental Symbols© and Dental Encoder© database in forensic odontology. J Forensic Sci 2012;57:206-11.  Back to cited text no. 38
    
39.
Silva RF, Nunes FG, Faria Neto JC, Rege IC, Daruge E Jr. Forensic importance of panoramic radiographs for human identification. RGO Rev Gaúch Odontol 2012;60:527-31.  Back to cited text no. 39
    
40.
Furst G, Happonen RP, Laaksonen H, Wallin A, Tammisalo T, Stimson PG. Use of orthopantomographs in forensic identification. Am J Forensic Med Pathol 1991;12:59-63.  Back to cited text no. 40
    
41.
Said EH, Nassar DE, Fahmy G, Ammar HH. Teeth segmentation in digitized dental X-ray films using mathematical morphology. IEEE Trans Inf Forensics Secur 2006;1:178-89.  Back to cited text no. 41
    
42.
Lin PL, Huang PY, Huang PW, Hsu HC, Chen CC. Teeth segmentation of dental periapical radiographs based on local singularity analysis. Comput Methods Programs Biomed 2014;113:433-45.  Back to cited text no. 42
    


    Figures

  [Figure 1], [Figure 2], [Figure 3]
 
 
    Tables

  [Table 1], [Table 2], [Table 3]



 

Top
 
 
  Search
 
Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

 
  In this article
Abstract
Introduction
Materials and Me...
Results
Discussion
Conclusions
References
Article Figures
Article Tables

 Article Access Statistics
    Viewed458    
    Printed14    
    Emailed0    
    PDF Downloaded62    
    Comments [Add]    

Recommend this journal