• Home
  • Sitemap
  • Contact Us

open access eISSN 2093-3673

Journal
Impact Factor

1.4

Article View

Original Article

Anat Cell Biol 2024; 57(4): 535-542

Published online December 31, 2024

https://doi.org/10.5115/acb.24.114

Copyright © Korean Association of ANATOMISTS.

A new metric method for sex estimation using three-dimensional imaging of the nuchal crest

Yun taek Shim1 , Ye Hwon Jeong1 , Nahyun Aum1 , Hong-il Ha1 , Minsung Choi1 , Jin young Hyun1 , Ho-seung Lee1 , Yi-Suk Kim2

1Division of Forensic Medicine, National Forensic Service Seoul Institute, Seoul, 2Department of Anatomy, The Catholic Institute for Applied Anatomy, College of Medicine, The Catholic University of Korea, Seoul, Korea

Correspondence to:Yun taek Shim
Division of Forensic Medicine, National Forensic Service Seoul Institute, Seoul 08036, Korea
E-mail: rino333@korea.kr

Received: April 29, 2024; Revised: July 15, 2024; Accepted: July 15, 2024

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

In Walker’s nonmetric method, the nuchal crest serves as the representative region for indicating sexual dimorphism in cranial bones. However, the accuracy of sex estimation using the nuchal crest is lower than that using other anatomical regions. Furthermore, because of the protruding processes and structurally challenging features characterized by uneven and rough surfaces, there is a lack of metric methods for sex estimation, making quantification challenging. In this study, we aimed to validate a derived metric method for sex estimation by reconstructing the nuchal crest region in three-dimensional (3D) images obtained from computed tomography scans of cranial bones and compare its accuracy with that of the nonmetric method. A total of 648 images were collected, with 100 randomly selected for use in the nonmetric method. We applied our metric method to the remaining 548 images. Our findings showed that the surface area of the nuchal crests was greater in male individuals than in female individuals. The nuchal crest surface area quantified by the metric method increased the accuracy of sex estimation by 48% compared with that by the nonmetric method. Our metric method for sex estimation, which quantifies the nuchal crest surface area using 3D images of the skull, led to a high sex estimation accuracy of 93%. Future studies should focus on proposing and quantifying new measurement methods for areas showing sexual characteristics in the skull that are difficult to measure, thereby enhancing the accuracy and reliability of sex estimation in human skeletal identification across various fields.

Keywords: Three-dimensional reconstruction images, Computed tomography images, Metric method, Nuchal crest, Sex estimation

The morphological characteristics of bones play a crucial role in forensic anthropology for sex estimation and differentiation among racial groups [1]. Typically, when intact skeletal remains are available, the skull and pelvic bones are the most reliable indicators of sex. Classification accuracies of 92% and 95% can be achieved using the skull and pelvic bone, respectively. Combining both increases the accuracy to 98%, reaching 100% when the entire skeleton is present [2]. Among various skeletal structures, the skull undergoes the least structural changes owing to environmental factors, allowing the examination of morphological variations resulting from genetic factors and sexual dimorphism [3, 4]. Although male individuals generally have larger skulls and stronger muscle attachments than female individuals, these patterns may vary significantly in certain populations, even within geographically restricted areas and historical periods [5, 6].

Moreover, the occurrence of intact bones in forensic anthropological analyses is considerably less frequent than that of damaged bones [7, 8]. The accuracy of sex estimation diminishes when cranial bones, especially the skull, are found in a partially or completely damaged state [9, 10]. Therefore, sex estimation methods specific to distinct regions of the skull where sexual dimorphism is prominent are necessary.

A commonly employed morphological sex estimation method in forensic anthropology is Walker’s scoring system, which relies on five regions proposed by Buikstra and Ubelaker (i.e., the nuchal crest, mastoid process, supraorbital ridge, glabella, and mental eminence) [11]. The thickness and distinct characteristics of the nuchal crest, particularly the occipital bone, make it less susceptible to damage, and scoring is based on the smoothness of the nuchal surface. A smooth nuchal surface with minimal external occipital protuberance (EOP) is scored as 1 point, whereas a rough surface with prominent EOP is scored as 5 points [11, 12]. Owing to the three-dimensional (3D) structure of the skull, characterized by irregular shapes and surfaces, visually capturing subtle sexual dimorphic changes is challenging, and sexual dimorphic features are often measured through meticulous methods [13]. Additionally, nonmetric sex estimation methods require high expertise, are more subjective than metric methods, and carry the risk of additional damage when visual or manual measurements of actual bones are used.

Reconstructing cranial computed tomography (CT) images into 3D images allows the measurement of small or internal structures that are difficult to measure, providing a higher level of objectivity [8]. The 3D reconstruction of cranial images enables easy rotation and analysis along multiple axes, allows data accumulation without damaging tissues, and facilitates repeated examinations and analyses [14]. Consequently, recent research in fields such as forensic medicine, forensic anthropology, archaeology, and palaeobiology has explored both nonmetric and metric methods using 3D reconstructed CT images [7, 15, 16]. However, there is currently a lack of metric sex estimation studies for the nuchal crest region owing to challenges associated with measuring protrusions and rough surfaces.

Therefore, in this study, we attempted to measure the range of nuchal crests measurement by reconstructing the nuchal crests CT image in 3D, derive a logistic regression equation to determine whether the measured value is of a male or female individual, and verify its effectiveness.

This study used 648 skull CT images of deceased Korean adults (aged ≥20 years) who underwent forensic post-mortem (PM) autopsy at the National Forensic Service Seoul Institute. The equipment used to acquire the 648 CT images was a PMCT device (SOMATOM AS+, Siemens Healthineers), which is commonly used for forensic evaluations. Whole-body scans were performed using an imaging method. The Digital Imaging and Communication in Medicine files obtained from the PMCT examinations were processed using the Materialise’s Interactive Medical Image Control System (MIMICS) 24.0 program (Materialise NV) to extract cranial bone images within the Hounsfield unit range of 226–3,071. The images were converted into computer-aided design format. The Frankfort horizontal plane was established as the x-axis plane, the frontal plane as the y-axis plane, and the sagittal plane as the z-axis plane using 3-matic 16.0 MIMICS (Materialise NV) to anatomically align the cranial bones (Fig. 1) [16].

Figure 1. Three-dimensional reconstruction model used for nonmetric estimation. (A–C) Left, right, and occipital planes of a skull from a male individual. (D–F) Left, right, and occipital planes of a skull from a female individual.

The selection criterion included an intact skull with no apparent deformities or damage on CT images. Of the 648 images, a sample of 548, excluding 100 randomly selected images, was used to derive a sex estimation regression equation.

For the metric method, all 548 images were processed using 3-matic 16.0 to define the measurement range of the nuchal crests and measure the surface area. To measure the surface area of the nuchal crests, the most prominent point at the EOP in the sagittal plane was used as the landmark. The superior measurement boundary was established 2 cm above the reference point, whereas the measurement boundaries on both sides were extended 2 cm in their respective directions. The lower measurement boundary was set 1 cm vertically downward from the point where a sagittal plane passing directly through the measurement reference point intersects with the line of the inferior nuchal crests (Fig. 2). The measured values of the nuchal crest surface area were subjected to logistic regression analysis using SPSS version 25 (IBM Co.) to derive the regression equation.

Figure 2. The nuchal crest measurement range (A–C).

To validate the effectiveness of the sex estimation equation derived using metric methods, both nonmetric and metric methods were employed. Initially, a nonmetric method was employed wherein 100 randomly selected 3D images were observed by rotating them using a previously proposed method [13]. Sex estimation based on the nuchal crests was performed through two separate assessments spaced 3 months apart by the forensic anthropological examiner (Dr. Yi-Suk Kim) of this institution, with the nuchal crests being scored on a scale ranging from 1 to 5 points. A score close to 1 point was assigned to smaller or smoother nuchal crests, whereas a score close to 5 points was assigned to larger or rougher nuchal crests (Fig. 3). If both the first and second nonmetric sex estimations resulted in scores of 4–5 points, the sex was classified as male, and if the scores were of 1–2 points, the sex was classified as female. If a score of 3 points was obtained in the first or second assessment or if the first and second assessments did not match, the classification was marked as “unknown.” Then, the results were compared with the known individual’s sex to assess the accuracy of the nonmetric method.

Figure 3. Standard of the nuchal crest for scoring traits of the skull. From Buikstra and Ubelaker [13].

Subsequently, using the identical set of 100 images subjected to the nonmetric methods, the metric approach was performed. The metric method results were compared with the known individual’s sex to evaluate the accuracy of the metric method, which was further compared with the accuracy of sex estimation achieved through the nonmetric method. Metric measurements on all 648 images used in this study were performed by PhD. Yun taek Shim and Ms. Ye Hwon Jeong, and a paired t-test was used to confirm that there was no significant difference between the two measurements.

Statistical analysis was conducted using SPSS version 25. Personal information and the sex of the deceased individuals used in the study were kept confidential, and ethical approval was obtained from the National Institute of Scientific Investigation Ethics Committee (approval No. 2021-05-HR). The requirement for informed consent was waived because the study involved exempted individuals.

The study population included 356 male and 292 female individuals (average age, 49.1 and 49 years, respectively) (Table 1). In total, 548 nuchal crest surface areas were measured using reconstructed 3D images. A regression equation was derived from these measurements, and its validity was assessed by applying it to the surface area measurements of 100 images previously evaluated using nonmetric methods. This process allowed for the determination of sex estimation accuracy. Subsequently, the accuracy of sex estimation obtained through the nonmetric method was compared with that of the metric method.

Table 1 . Descriptive statistics of individual’s age

SexNon-metric methodMetric method
No. of casesYearsNo. of casesYears
Male5138.9±13.130550.8±14.9
Female4939.2±13.324350.5±17.6
Total10039.0±13.154850.8±15.2

Values are presented as number only or mean±SD.



Nonmetric measurements

The 100 images used for nonmetric methods were obtained from 51 male individuals and 49 female individuals (average age, 38.9 and 39.2 years, respectively) (Table 1). The relationship between the primary and second estimations according to sex was statistically analyzed (Table 2).

Table 2 . Sexual distribution of nuchal crest using the non-metric method

TypeNuchal crest
Male (n=51)Female (n=49)
PESEPESE
1 point0 (0)1 (2.0)14 (28.6)21 (42.9)
2 points4 (7.8)9 (17.6)18 (36.7)19 (38.8)
3 points22 (43.1)24 (47.1)13 (26.5)9 (18.4)
4 points22 (43.1)13 (25.5)4 (8.2)0 (0)
5 points3 (5.9)4 (7.8)0 (0)0 (0)
χ25.4676.154
df43
P-value0.2430.104

Values are presented as number (%). PE, primary estimation; SE, secondary estimation.



In the nonmetric primary assessment, sex estimation accuracy showed 57 cases (57%) of match, 35 cases (35%) of “unknown,” and eight cases (8%) of mismatch. When divided by sex, female individuals exhibited a matching rate of 65% (32/49), whereas male individuals had a matching rate of 49% (25/51). In secondary assessments, there were 56 cases (56%) of match, 33 cases (33%) of “unknown,” and 11 cases (11%) of mismatch. When divided by sex, female individuals exhibited a matching rate of 80% (39/49), whereas males had a matching rate of 33% (17/51). In the final sex estimation incorporating both primary and secondary assessments, there were 45 cases (45%) of match, 53 cases (53%) of “unknown,” and two cases (2%) of mismatch. Among male individuals, 25% (13/51) were matched, and among female individuals, 65% (32/49) were matched.

Metric measurements

The 548 images used in deriving the metric regression equation were obtained from 305 male individuals and 243 female individuals (average age shown in Table 1; 50.8 and 50.5 years, respectively).

All metric measurements were performed by two measurers once each, and statistical analysis performed using the paired t-test confirmed no significant differences in the measurement values between the two measurements (Table 3). The statistical analysis of the metric method results revealed an equation for estimating sex using the nuchal crest surface area (Table 4). The sectioning point was set at 0.5. When the nuchal crest surface measurement value is substituted, an odds value of ≥0.5 indicates as male and a value of <0.5 indicates female.

Table 3 . Paired t-test for measurement values by two measurers

Nuchal crest surface areaMeasurer (n=548)Measurer (n=100)P-value
1212
Male (mm2)2,882.85±253.992,882.87±253.892,895.28±176.212,895.26±175.73>0.05
Female (mm2)2,427.38±294.982,427.47±294.992,350.18±218.842,350.32±218.73>0.05
Total (mm2)2,680.88±354.462,680.93±354.402,628.18±337.502,628.24±337.27>0.05


Table 4 . Logistic regression results of the nuchal crest surface area

Discrimination equationSectioning pointSignificance
M=Exp (–15.456+0.006×nuchal crest surface)
Odds=M/(1–M)
F<0.5≤M0

M, male; F, female.



Moreover, as the nuchal crest surface area increased, the probability of being male also increased.

To validate the effectiveness of the derived regression equation, the surface area was measured using the metric method on 100 images previously assessed using the nonmetric method. Subsequently, sex estimation was performed by substituting the measured values into the regression equation and comparing the accuracy of sex estimation between the metric and nonmetric methods.

The metric sex estimation of 100 images showed actual sex matching in 93 cases (93%), with a matching rate of 100% (51/51) for male individuals and 86% (42/49) for female individuals.

In the nonmetric primary assessment, 94% (33/35) of the entities that scored 3 points matched the actual sex. In the secondary assessment, among the entities that scored 3 points, 94% (31/33) matched the actual sex. In the final sex estimation, among the entities classified as “unknown” (53 cases), 92% (49 cases) matched the actual sex.

Ultimately, the metric sex estimation showed an increase of 48 cases (48%) compared with the nonmetric method, with increases of 38 (38%) and 10 cases (10%) in males and females, respectively (Table 5).

Table 5 . Sex estimation accuracy comparison between non-metric and metric methods

SexNon-metric methodMetric method
Primary estimationSecondary estimationFinal estimation
MatchMismatchUnknownMatchMismatchUnknownMatchMismatchUnknownMatchMismatch
Male (n=51)25 (49)4 (8)22 (43)17 (33)10 (20)24 (47)13 (25)2 (4)36 (71)51 (100)0 (0)
Female (n=49)32 (65)4 (8)13 (27)39 (80)1 (2)9 (18)32 (65)0 (0)17 (35)42 (86)7 (14)
Total (n=100)57 (57)8 (8)35 (35)56 (56)11 (11)33 (33)45 (45)2 (2)53 (53)93 (93)7 (7)

Values are presented as number (%).


In this study, we validated the derived metric method for sex estimation by reconstructing the nuchal crest region in 3D images obtained from CT scans of the skulls of Korean adults and compared it with the nonmetric method.

Generally, the skulls of male individuals exhibit larger and more prominent features, whereas those of female individuals have softer and less pronounced landmarks [17]. Utilizing this, Walker [11] compared the characteristics of various landmarks, assigned scores, and performed sex estimation using the majority rule [18-20]. Although the nuchal crests are one of five representative regions indicating sexual dimorphism in the cranial bones, the accuracy of sex estimation using this region tends to be low compared with that using other regions. Ramsthaler et al. [21] analyzed skulls of Germans using CT scans and reported a sex estimation accuracy of 60% (male, 72.6%; female, 46.9%) when Knussmann’s non-measurement method was used for occipital protuberance analysis. Walker [11] also reported the second-lowest accuracy of 71.4% (male, 62.2%; female, 82.1%) when applying non-measurement-based sex estimation to the nuchal crests of skulls of modern American and English individuals. Jilala et al. [22], who conducted a non-measurement-based sex estimation on skulls of Tanzanian individuals, reported the lowest accuracy of 66% (male, 47%; female, 86%) for the nuchal crests among five regions, attributing this to cultural reasons influenced by growth environments. Skull characteristics vary across populations owing to nutritional status, environmental factors, and genetic influences affecting growth, and differences in the size, shape, and position of cranial landmarks used for sex estimation can lead to errors [23, 24]. Generally, Western populations exhibit more pronounced sex-specific features in their skulls than Asian populations do. Kim et al. [10] compared the skulls of Koreans with those of other populations using a measurement-based approach and stated that Korean male individuals had smaller skulls than European male individuals did, whereas Korean female individuals had larger skulls compared to Japanese and Indian female individuals. Additionally, in a non-measurement-based study, Kim et al. [12] reported that the overall occiput shape in Koreans was flatter, with more female individuals exhibiting a protruding shape than male individuals. Using Broca’s method to measure the degree of EOP, they reported that the criteria of “2 points” and “1 point,” which indicate female characteristics according to Walker’s standards, classified the sex as female in 78.8% and male in 65.3% of cases. Using our nonmetric method, sex estimation accuracy was lower for male individuals (25%) than for female individuals (65%). Mismatches were 4% for male individuals and 0% for female individuals, whereas unknown cases had a higher rate of misclassification, at 71% for male individuals and 35% for female individuals. Furthermore, the final nonmetric sex estimation exhibited an accuracy of 45%, which was lower than that observed in European, American, and African populations. This discrepancy was attributed to the high proportion of cases judged as “3 points” using the nonmetric method, which contributed to sex estimation errors and resulted in a significantly lower sex estimation accuracy compared with that of other populations.

In this study, when a score of 3 was judged as male in the primary and secondary sex estimation, the final sex estimation recorded 71 matches, 9 mismatches, and 9 cases of “unknown,” resulting in a 26% increase in sex accuracy (26 cases). Conversely, when a score of 3 was judged as female, the final sex estimation recorded 58 matches, 21 mismatches, and 21 cases of “unknown,” indicating a 13% increase in sex accuracy (13 cases).

This suggests that Korean males exhibit less pronounced sexual dimorphism in the nuchal crest than Western populations, leading to a higher likelihood of being classified as female or “unknown.”

The nuchal crest is discriminated based on the degree of protrusion of the occipital protuberance and roughness of the occipital surface [11, 13, 15]. The number of protruding bumps in the occipital region and the elevation difference, determined within the defined (limited) measurement range, signifies that if the surface is smooth (indicating female), it has a smaller surface area, whereas if it is rough and uneven (indicating male), the surface area is larger (Fig. 4). Therefore, we emphasized that the nuchal crests are a 3D structure with a protruding structure and rough surface, and we utilized a 3D image of the nuchal crests to conduct metric sex estimation.

Figure 4. Sexual dimorphism in the nuchal crest surface area: male (A, B), female (C, D). EOP, external occipital protuberance; INC, interior nuchal crest.

The metric method showed a sex estimation accuracy of 93%, and among the 53 cases classified as “unknown” using the nonmetric method, 49 (92%) were reclassified as matches. For male individuals, all 36 “unknown” cases were reclassified as matches (100%), whereas for female individuals, 13 of 17 were reclassified as matches (76%). The high accuracy of 93% in measurement-based discrimination was achieved by successfully quantifying the nuchal crests with our metric method and minimizing the impact of the “3 points,” which was challenging to distinguish visual error variability. However, it is noteworthy that all seven mismatched cases were observed in female individuals. This unusual finding is considered an estimation error caused by the characteristics of the Korean population, where female individuals have larger heads and more prominent occipital areas than male individuals do.

In conclusion, this study quantified the nuchal crest surface using 3D images of cranial bones, leading to a high sex estimation accuracy of 93% using the metric method. Owing to limitations in defining the measurement range for the entire nuchal crest surface, only a limited range, including the EOP, was measured. However, we believe that the challenging nature of measurements owing to structural characteristics suggests the introduction of a new metric method for sex estimation, which had not been utilized previously, and this measurement method may enhance the accuracy of sex estimation using the nuchal crests when applied to populations with stronger sexual dimorphism compared with the Korean population. In the future, it will be essential to propose and quantify new measurement methods for areas in the skull showing sexual characteristics that are difficult to measure, thereby enhancing the accuracy and reliability of sex estimation in human skeletal identification across various fields.

Conceptualization: YS. Data acquisition: YHJ, JH, HL. Data analysis or interpretation: YS, YHJ, YSK, HH. Drafting of the manuscript: YS. Critical revision of the manuscript: YS, NA, MC. Approval of the final version of the manuscript: all authors.

No potential conflict of interest relevant to this article was reported.

This work was supported by the National Forensic Service (NFS2024MED06), Ministry of Interior and Safety, Korea.

  1. Sangvichien S, Boonkaew K, Chuncharunee A, Komoltri C, Udom C, Chandee T. Accuracy of cranial and mandible morphological traits for sex determination in Thais. Siriraj Med J 2008;60:240-3.
  2. Krogman WM, Isçan MY. The human skeleton in forensic medicine. 2nd ed. Charles C Thomas; 1986.
  3. Passey J, Mishra SR, Singh R, Sushobhna K, Singh S, Sinha P. Sex determination using mastoid process. Asian J Med Sci 2015;6:93-5.
    CrossRef
  4. Sobhani F, Salemi F, Miresmaeili A, Farhadian M. Morphometric analysis of the inter-mastoid triangle for sex determination: application of statistical shape analysis. Imaging Sci Dent 2021;51:167-74.
    Pubmed KoreaMed CrossRef
  5. Cunha E, van Vark GN. The construction of sex discriminant functions from a large collection of skulls of known sex. Int J Anthropol 1991;6:53-66.
    CrossRef
  6. Kemkes A, Göbel T. Metric assessment of the "mastoid triangle" for sex determination: a validation study. J Forensic Sci 2006;51:985-9.
    Pubmed CrossRef
  7. Santarelli C, Argenti F, Uccheddu F, Alparone L, Carfagni M. Volumetric interpolation of tomographic sequences for accurate 3D reconstruction of anatomical parts. Comput Method Progr Biomed 2020;194:105525.
    Pubmed CrossRef
  8. Simmons-Ehrhardt TL, Ehrhardt CJ, Monson KL. Evaluation of the suitability of cranial measurements obtained from surface-rendered CT scans of living people for estimating sex and ancestry. J Forensic Radiol Imaging 2019;19:100338.
    CrossRef
  9. Peckmann TR, Orr K, Meek S, Manolis SK. Sex determination from the talus in a contemporary Greek population using discriminant function analysis. J Forensic Leg Med 2015;33:14-9.
    Pubmed CrossRef
  10. Kim DI, Lee UY, Han SH. Sex determination using three-dimensional image of skull in Korean: metric study by discriminant function analysis. Korean J Phys Anthropol 2015;28:103-18.
    CrossRef
  11. Walker PL. Sexing skulls using discriminant function analysis of visually assessed traits. Am J Phys Anthropol 2008;136:39-50.
    Pubmed CrossRef
  12. Kim DI, Han SH. Non-metric study of the external occipital protuberance for sex determination in Koreans: using three-dimensional reconstruction images. Korean J Phys Anthropol 2015;28:239-45.
    CrossRef
  13. Buikstra JE, Ubelaker DH. Standards for data collection from human skeletal remains: proceedings of a seminar at the field Museum of Natural History organized by Jonathan Haas. Arkansas Archeological Survey; 1994.
  14. Teodoru-Raghina D, Perlea P, Marinescu M. Forensic anthropology from skeletal remains to CT scans: a review on sexual dimorphism of human skull. Rom J Leg Med 2017;25:287-92.
    CrossRef
  15. Shim YT, Jeong YH, Kim YS, Aum N, Choi SG, Oh SM, Park JH, Kim DY, Koo HN. Estimation of forensic sex based on three-dimensional reconstruction of skull in Korean: non-metric study. Korean J Leg Med 2021;45:79-86.
    CrossRef
  16. Jeong YH, Koo HN, Kim YS, Lee B, Kim S, Shim YT. Using 3D images of Korean's mastoid process to estimate sex: a metric study. Forensic Imaging 2022;31:200527.
    CrossRef
  17. Kim HJ, Kim KD, Choi JH, Hu KS, Oh HJ, Kang MK, Hwang YI. Differences in the metric dimensions of craniofacial structures with aging in Korean males and females. Korean J Phys Anthropol 1998;11:197-212.
    CrossRef
  18. Stevenson JC, Mahoney ER, Walker PL, Everson PM. Technical note: prediction of sex based on five skull traits using decision analysis (CHAID). Am J Phys Anthropol 2009;139:434-41.
    Pubmed CrossRef
  19. Lewis CJ, Garvin HM. Reliability of the walker cranial nonmetric method and implications for sex estimation. J Forensic Sci 2016;61:743-51.
    Pubmed CrossRef
  20. Garvin HM, Sholts SB, Mosca LA. Sexual dimorphism in human cranial trait scores: effects of population, age, and body size. Am J Phys Anthropol 2014;154:259-69.
    Pubmed CrossRef
  21. Ramsthaler F, Kettner M, Gehl A, Verhoff MA. Digital forensic osteology: morphological sexing of skeletal remains using volume-rendered cranial CT scans. Forensic Sci Int 2010;195:148-52.
    Pubmed CrossRef
  22. Jilala W, Ng'walali P, Russa D, Bushozi P. Sexing contemporary Tanzanian skeletonized remains using skull morphology: a test of the walker sex assessment method. Forensic Sci Int Rep 2021;3:100195.
    CrossRef
  23. Saini V, Srivastava R, Rai RK, Shamal SN, Singh TB, Tripathi SK. Sex estimation from the mastoid process among North Indians. J Forensic Sci 2012;57:434-9.
    Pubmed CrossRef
  24. Sharma BB, Nidugala H, Avadhani R. Mastoid process-a tool for sex determination, an anatomical study in South Indian skulls. Int J Biomed Res 2013;4:106-10.
    CrossRef

Share this article on :