ArticleAmerican journal of biological anthropology2022
An osteometric and 3D analysis of the atlanto-occipital joint: An initial screening method to exclude crania and atlases in commingled remains.
Article in American journal of biological anthropology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 13 citations in OpenAlex.
- Morphological analysis of occipital condyle and superior articular facet of first cervical vertebra and its congruence in a Thai population.Anatomy & cell biology · 2025Article
- An examination of commingled first tarsometatarsal and atlantoaxial joints by deviation analysis.Journal of forensic sciences · 2025Article
- An exclusionary screening method based on 3D morphometric features to sort commingled atlases and axes.Scientific reports · 2024Article
- Article
- Digital pair-matching of iliac bones: pilot study on a three-dimensional approach with models acquired through stereophotogrammetry.International journal of legal medicine · 2023Article
- Article
- An osteometric and 3D analysis of the atlanto-occipital joint: An initial screening method to exclude crania and atlases in commingled remains.American journal of biological anthropology · 2022Article
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesThe anatomical features of the atlanto-occipital joint can be potentially useful in re-associating or excluding crania to atlases in commingled remains. This study investigated whether linear measurements and the 3-dimensional (3D) surface of occipital condyles and articular facets of atlases can represent valid insights for this purpose.
methodsThe variations among eight corresponding linear distances were analyzed in a sample of 150 individuals through six supervised machine learning techniques attempting to develop classifiers able to identify elements belonging to the same individual. Furthermore, a 3D analysis was conducted on the articular surfaces through superimpositions of 3D models of corresponding and non-corresponding crania and atlases obtained by using respectively stereophotogrammetry and laser scanning. This analysis investigated differences in terms of point-to-point distances (Root Mean Square, RMS) of superimposed 3D surfaces.
resultsNone of the six machine learning techniques were able to correctly detect a satisfying percentage of correspondent pairs in the overall sample by using the linear variables. The 3D analysis of the articular surfaces found RMS values over 0.53 mm only for superimposed non-corresponding surfaces, which sets a threshold value to identify 32% of incorrect pairs. DISCUSSION: The re-association of cranium to atlas proved to be challenging and hardly possible when considering only metric variables. However, the 3D geometry of the articular surfaces represents a valid variable for this purpose and 3D analyses pave the way for an initial exclusion of incorrect re-associations, thus should not be considered as a re-association method per se, but as an exclusionary screening technique.
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