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Updated: May 20, 2026

Outer-Boundary Assisted Segmentation and Quantification of Trabecular Bones by an Imagej Plugin

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Datasets for acquiring 3D bone shapes: a systematic review.

Seyed Hamidreza Alavi¹, Gabriëlle J M Tuijthof¹, Nico J J Verdonschot²

¹Department of Biomechanical Engineering, University of Twente, the Netherlands.

Journal of Biomechanics

|April 12, 2026

Summary

This summary is machine-generated.

Finding 3D human bone shape datasets is challenging due to scattered sources. This study identifies 152 datasets, highlighting a need for better organization and more mesh/CAD models for research.

Keywords:

3D model 3D shape Bone CT Dataset MRI

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Area of Science:

Biomedical Engineering
Medical Imaging
Data Science

Background:

Three-dimensional (3D) human bone shapes are critical for engineering, preclinical, and clinical applications.
Existing 3D bone datasets are fragmented across numerous sources with inconsistent documentation, hindering accessibility.

Purpose of the Study:

To systematically identify and analyze publicly available datasets containing 3D human bone shapes or imaging data (CT/MRI) suitable for generating 3D models.
To provide a comprehensive overview of the current landscape of these datasets, including their specifications and limitations.

Main Methods:

A systematic search was performed across academic databases (Scopus, Web of Science, PubMed), data repositories (Zenodo, Mendeley Data), and the Grand Challenge platform.
Dataset specifications, including data formats, imaged regions, modalities, subject metadata, and usage policies, were extracted and analyzed.

Main Results:

152 datasets covering over 371,000 subjects were identified. Of these, 44 contained 3D bone shapes, primarily as voxel segmentation masks (30 datasets) or surface meshes (5 datasets).
No datasets offered computer-aided design (CAD) models. The spinal column was the most represented anatomical region (28 datasets), while the thorax was the least (10 datasets).

Conclusions:

Publicly available 3D bone shape datasets are highly dispersed, complicating their discovery and use.
A significant gap exists in the availability of mesh and CAD models, which are crucial for advancing orthopaedic, biomechanical, and engineering research.
This review consolidates dataset specifications into a guide (github.com/BoneHub/Public-Datasets) to improve resource identification, comparison, and utilization.