A conditional generative diffusion model of trabecular bone with tunable microstructure
The proposed generative model is capable of generating realistic digital trabecular bones that can be precisely tuned to achieve specified microstructural characteristics. Possible applications include virtual clinical trials of new skeletal image biomarkers and establishing priors for advanced image reconstruction.
Authors
- Tianyi Ye (ORCID: https://orcid.org/0009-0004-4097-2864)
- Adam D. Sylvester (ORCID: https://orcid.org/0000-0002-5234-074X)
- Xin Wang (ORCID: https://orcid.org/0009-0003-9785-1791)
- Aswath Sivakumar
- Gengxin Shi
- Web Stayman (ORCID: https://orcid.org/0000-0003-4358-378X)
- Wojtek Zbijewski (ORCID: https://orcid.org/0000-0001-7593-5394)
Institutions
- Johns Hopkins University (US)
- Johns Hopkins Medicine (US)
Publication Details
- Published
- 2025-04-02
- DOI
- https://doi.org/10.1117/12.3049125
- Primary Topic
- Advanced Mathematical Modeling in Engineering
- Type
- article
- Field-Weighted Citation Impact
- 0.00