ArticleInternational journal of legal medicine2020
Advanced procedures for skull sex estimation using sexually dimorphic morphometric features.
Article in International journal of legal medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
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Who cites it
25 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence in forensic science: a systematic review. Part I: personal identification.International journal of legal medicine · 2026Pooled it
- Machine learning algorithms in the estimation of sex from 3DCT-generated cranial and pelvic measurements.International journal of legal medicine · 2026Article
- Automated skull orientation classification in Thai population using CNN-based transfer learning.Scientific reports · 2026Article
- Tracing asymmetry and sexual dimorphism in the adult iliac auricular surface: a geometric morphometrics and machine learning approach.International journal of legal medicine · 2026Article
- Sex classification using exocranial surfaces in a multi-population sample.International journal of legal medicine · 2026Article
- Coupling geometric morphometrics and machine learning for mandibular sex estimation in Late Pleistocene and Late Modern populations.Scientific reports · 2025Article
- Sex estimation through the lens of cross-sectional geometric properties of the ulna.Forensic sciences research · 2025Article
- Discriminant function analysis of maxillary bone measurements for sex estimation in a Colombian population by using cone-beam computed tomography.The Journal of forensic odonto-stomatology · 2025Article
- Geometric morphometrics approach for classifying children's nutritional status on out of sample data.Scientific reports · 2025Article
- Classification performance of the Sella-Tunis et al. (2017) sex estimation method in Czech population: different posterior probability threshold approaches.International journal of legal medicine · 2024Article
- Sex determination through maxillary dental arch and skeletal base measurements using machine learning.Head & face medicine · 2024Article
- Prioritizing a high posterior probability threshold leading to low error rate over high classification accuracy: the validity of MorphoPASSE software for cranial morphological sex estimation in a contemporary population.International journal of legal medicine · 2024Article
- Mandibular and dental measurements for sex determination using machine learning.Scientific reports · 2024Article
- Artificial intelligence model for predicting sexual dimorphism through the hyoid bone in adult patients.PloS one · 2024Article
- Sex estimation techniques based on skulls in forensic anthropology: A scoping review.PloS one · 2024Article
- A new method for sex estimation based on femoral cross-sectional geometry measurements and its validation using recent and ancient populations.International journal of legal medicine · 2023Article
- The cranial capacity of the Saudi population measured using 3D computed tomography scans.Neurosciences (Riyadh, Saudi Arabia) · 2023Article
- Machine learning and discriminant function analysis in the formulation of generic models for sex prediction using patella measurements.International journal of legal medicine · 2023Article
- Preparing computed tomography images for machine learning in forensic and virtual anthropology.Forensic science international. Synergy · 2023Article
- Sexual dimorphism in shape and size of the neurocranium.International journal of legal medicine · 2022Article
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4 authors.
Funding
Abstract
This paper introduces an automated method for estimating sex from cranial sex diagnostic traits by extracting and evaluating specialized morphometric features from the glabella, the supraorbital ridge, the occipital protuberance, and the mastoid process. The proposed method was developed and evaluated using two European population samples, a Czech sample comprising 170 crania reconstructed from anonymized CT scans and a Greek sample of 156 crania from the Athens Collection. It is based on a fully automatic algorithm applied on 3D models for extracting sex diagnostic morphometric features which are further processed by computer vision and machine learning algorithms. Classification accuracy was evaluated in a population specific and a population generic 2-way cross-validation scheme. Population-specific accuracy for individual morphometric features ranged from 78.5 to 96.7%, whereas population generic correct classification ranged from 71.7 to 90.8%. Combining all sex diagnostic traits in multi-feature sex estimation yielded correct classification performance in excess of 91% for the entire sample, whereas the sex of about three fourths of the sample could be determined with 100% accuracy according to posterior probability estimates. The proposed method provides an efficient and reliable way to estimate sex from cranial remains, and it offers significant advantages over existing methods. The proposed method can be readily implemented with the skullanalyzer computer program and the estimate_sex.m GNU Octave function, which are freely available under a suitable license.
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