Gender Prediction From Foramen Magnum Using Machine Learning Algorithms

Abstract

Aim; Accurate and highly accurate postmortem identification of the individual is important for forensic sciences. The main element of identification is the determination of gender. The aim of this study is to predict gender with high accuracy using Machine learning (ML) algorithms with parameters of the foramen magnum obtained from Computed Tomography (CT) images. Method; The study was performed on CT images of 214 individuals aged 18-65 years. For. magnum length, width, circumference and area were measured on the images. The measurements were used in ML algorithms for gender prediction and performance values were recorded. Results; As a result of the study, gender prediction results with high accuracy up to 0.84 were obtained with ML algorithms. In addition, it was found that the for. magnum height parameter contributed the most to this high rate with the SHapley Additive exPlanations analyzer. Conclusion; As a result of our study, it was found that the parameters obtained from for. magnum can be used for sex prediction in the Turkish population by analyzing them with ML algorithm. In this respect, we think that it will contribute to other metric studies in the Turkish population.

Keywords

• Foramen magnum
• computed tomography
• machine learning algorithms
• gender prediction

Gender Prediction From Foramen Magnum Using Machine Learning Algorithms

Öz

Giriş ve Amaç: Bireyin ölüm sonrası doğru ve yüksek doğrulukta kimliklendirilmesi adli bilimler için önemlidir. Kimlik tespitinin ana unsuru ise cinsiyetin belirlenmesidir. Bu çalışmanın amacı, Bilgisayarlı Tomografi (BT) görüntülerinden elde edilen foramen magnum parametreleri ile Makine öğrenimi (ML) algoritmalarını kullanarak cinsiyeti yüksek doğrulukla tahmin etmektir. Gereç ve Yöntemler: Çalışma 18-65 yaş arası 214 bireyin BT görüntüleri üzerinde gerçekleştirilmiştir. Görüntüler üzerinde for. magnum uzunluğu, genişliği, çevresi ve alanı ölçülmüştür. Ölçümler cinsiyet tahmini için ML algoritmalarında kullanıldı ve performans değerleri kaydedildi. Bulgular: Çalışma sonucunda ML algoritmaları ile 0,84'e varan yüksek doğrulukta cinsiyet tahmin sonuçları elde edilmiştir. Ayrıca SHapley Additive exPlanations analizörü ile bu yüksek orana en çok for. magnum yükseklik parametresinin katkı sağladığı tespit edilmiştir. Sonuç: Çalışmamız sonucunda for. magnum'dan elde edilen parametrelerin ML algoritması ile analiz edilerek Türk popülasyonunda cinsiyet tahmini için kullanılabileceği tespit edilmiştir. Bu açıdan Türk popülasyonunda yapılacak diğer metrik çalışmalarına katkı sağlayacağını düşünüyoruz.

Anahtar Kelimeler

• Foramen magnum
• bilgisayarlı tomografi
• makine öğrenmesi algoritmaları
• cinsiyet tahmini

Kaynakça

1. 1. Babu YR, Kanchan T, Attiku Y, Dixit PN, Kotian M. Sex estimation from foramen magnum dimensions in an Indian population. Journal of forensic and legal medicine. 2012;19(3):162-7.
2. 2. Toneva D, Nikolova S, Harizanov S, Georgiev I, Zlatareva D, Hadjidekov V, et al. Sex estimation by size and shape of foramen magnum based on CT imaging. Legal Medicine. 2018;35:50-60.
3. 3. Kartal E, Etli Y, Asirdizer M, Hekimoglu Y, Keskin S, Demir U, et al. Sex estimation using foramen magnum measurements, discriminant analyses and artificial neural networks on an eastern Turkish population sample. Legal Medicine. 2022;59:102143.
4. 4. Fernandes ALVC, Shetti A, Lagali-Jirge V, Keluskar V. Accuracy of sex estimation by morphometric evaluation of foramen magnum using computed tomography–a systematic review and meta-analysis. Forensic Science, Medicine and Pathology. 2024;20(1):268-79.
5. 5. Meral O, Toklu BB, Meydan R, Kaya A, Karadayı B, Acar T. Sex estimation from foramen magnum parameters in adult Turkish population: A computed tomography study. Legal Medicine. 2020;47:101775.
6. 6. Secgin Y, Oner Z, Turan MK, Oner S. Gender prediction with the parameters obtained from pelvis computed tomography images and machine learning algorithms. Journal of the Anatomical Society of India. 2022;71(3):204-9.
7. 7. Singh A, Thakur N, Sharma A, editors. A review of supervised machine learning algorithms. 2016 3rd international conference on computing for sustainable global development (INDIACom); 2016: Ieee.
8. 8. Senol D, Secgin Y, Duman BS, Toy S, Oner Z. Sex and age estimation with machine learning algorithms with parameters obtained from cone beam computed tomography images of maxillary first molar and canine teeth. Egyptian Journal of Forensic Sciences. 2023;13(1):27.

9. 9. Erkartal HŞ, Tatlı M, Secgin Y, Toy S, Duman BS. Gender Estimation with Parameters Obtained From the Upper Dental Arcade by Using Machine Learning Algorithms and Artificial Neural Networks. European Journal of Therapeutics. 2023;29(3):352-8.
10. 10. Saez Y, Baldominos A, Isasi P. A comparison study of classifier algorithms for cross-person physical activity recognition. Sensors. 2016;17(1):66.
11. 11. Attia MH, Attia MH, Farghaly YT, Abulnoor BAE-S, Curate F. Performance of the supervised learning algorithms in sex estimation of the proximal femur: A comparative study in contemporary Egyptian and Turkish samples. Science & Justice. 2022;62(3):288-309.
12. 12. Kuan Y-C, Hong C-T, Chen P-C, Liu W-T, Chung C-C. Logistic regression and artificial neural network-based simple predicting models for obstructive sleep apnea by age, sex, and body mass index. Math Biosci Eng. 2022;19(11):11409-21.
13. 13. Seifert Z, Friedl L, Chaumoitre K, Brůžek J. Applicability and limitations of sex assessment based on foramen magnum. Forensic science international. 2017;271:126. e1-. e9.
14. 14. Navega D, Vicente R, Vieira DN, Ross AH, Cunha E. Sex estimation from the tarsal bones in a Portuguese sample: a machine learning approach. International journal of legal medicine. 2015;129:651-9.
15. 15. Toy S, Secgin Y, Oner Z, Turan MK, Oner S, Senol D. A study on sex estimation by using machine learning algorithms with parameters obtained from computerized tomography images of the cranium. Scientific Reports. 2022;12(1):4278.
16. 16. Gapert R, Black S, Last J. Sex determination from the foramen magnum: discriminant function analysis in an eighteenth and nineteenth century British sample. International journal of legal medicine. 2009;123:25-33.
17. 17. Edwards K, Viner M, Schweitzer W, Thali MJ. Sex determination from the foramen magnum. Journal of forensic radiology and imaging. 2013;1(4):186-92.
18. 18. Mehta M, Saini V, Patel M, Menon S. Applicability and reliability of foramen magnum for sex determination in contemporary Western Indian population: A computed tomographic study. Journal of Forensic Radiology and Imaging. 2019;17:31-5.
19. 19. Atreya A, Shrestha R, Bhandari K, Malla SK, Acharya S, Menezes RG. Morphometric analysis of the foramen magnum in sex estimation: An additional 3DCT study from Nepal on a larger sample. Health Science Reports. 2023;6(1):e999.
20. 20. Kalbouneh H, Mubarak N, Shwaqfeh J, Nawaiseh M, Ashour O, Alkhatib AM, et al. Estimation of sex from measurements of foramen magnum region in a contemporary Jordanian population: A computed tomographic study. Anthropologischer Anzeiger. 2021;78(4).
21. 21. Madadin M, Menezes RG, Al Saif HS, Alola HA, Al Muhanna A, Gullenpet AH, et al. Morphometric evaluation of the foramen magnum for sex determination: A study from Saudi Arabia. Journal of Forensic and Legal Medicine. 2017;46:66-71.