ArticleInternational journal of legal medicine2023
Stature estimation by semi-automatic measurements of 3D CT images of the femur.
Article in International journal of legal medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 14 citations in OpenAlex.
- Automated femoral measurement from postmortem computed tomographic images using artificial intelligence for forensic stature estimation in a Japanese population.International journal of legal medicine · 2026Article
- AI-driven differentiation of 2D proximal femur morphometry and hounsfield units for integrated forensic estimation of sex, stature, and age in a modern Thai dry bone sample.Anatomical science international · 2026Article
- Identification of Occupations in Different Populations Based on Skin Microbial Characteristics.Current microbiology · 2025Article
- Sex estimation from skull measurements of a contemporary Japanese population using three-dimensional computed tomography images.International journal of legal medicine · 2025Article
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Authors and funding
14 authors at 1 institution in 1 country.
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Abstract
Stature estimation is one of the most basic and important methods of personal identification. The long bones of the limbs provide the most accurate stature estimation, with the femur being one of the most useful. In all the previously reported methods of stature estimation using computed tomography (CT) images of the femur, laborious manual measurement was necessary. A semi-automatic bone measuring method can simplify this process, so we firstly reported a stature estimation process using semi-automatic bone measurement software equipped with artificial intelligence. Multiple measurements of femurs of adult Japanese cadavers were performed using automatic three-dimensional reconstructed CT images of femurs. After manually setting four points on the femur, an automatic measurement was acquired. The relationships between stature and five femoral measurements, with acceptable intraobserver and interobserver errors, were analyzed with single regression analysis using the standard error of the estimate (SEE) and the coefficient of determination (R
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