BoneDat, a database of standardized bone morphology for in silico analyses.

Abstract

In silico analysis is key to understanding bone structure-function relationships in orthopedics and evolutionary biology, but its potential is limited by a lack of standardized, high-quality human bone morphology datasets. This absence hinders research reproducibility and the development of reliable computational models. To overcome this, BoneDat has been developed. It is a comprehensive database containing standardized bone morphology data from 278 clinical lumbopelvic CT scans (pelvis and lower spine). The dataset includes individuals aged 16 to 91, balanced by sex across ten age groups. BoneDat provides curated segmentation masks, normalized bone geometry (volumetric meshes), and reference morphology templates organized by sex and age. By offering standardized reference geometry and enabling shape normalization, BoneDat enhances the repeatability and credibility of computational models. It also allows for integrating other open datasets, supporting the training and benchmarking of deep learning models and accelerating their path to clinical use.