Work

Three-dimensional deep-learning age and sex estimation from the fourth rib: de-identified CT-derived surface dataset and reference implementation

Year: 2026

Type: dataset

Abstract: 453 de-identified right fourth-rib surface meshes (binary STL, millimetres) segmented from clinical thin-section thoracic CT of adults aged 18-100 years (225 men, 228 women), labelled with sex and age only, with a frozen development/test split, 30 repeat segmentations for intra-observer analysis, and the complete deep-learning pipeline (multi-view RGB-D CNN, PointNet++, morphometric scalars, label-distribution learning, calibrated likelihood-ratio reporting) used in the accompanying Forensic Science International article. Data: CC BY 4.0; code: MIT.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.21864405

Authors: Etli, Yasin, ÖZDİL, AHMET

Institution: Ostim Technical University

Language: English

Topic: Forensic Anthropology and Bioarchaeology Studies

Subfield: Archeology (arts and humanities)

Field: Arts and Humanities

Domain: Social Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W7202056434

Cites:

Cited by:

Related to: 10