BoneX-ray computed tomography

Soar, Peter ORCID: 0000-0003-1745-9443 , Dall’Ara, Enrico, Palanca, Marco and Tozzi, Gianluca (2024) Data-driven image mechanics (D2IM): a deep learning approach to predict displacement and strain fields from undeformed X-ray tomography images – Evaluation of bone mechanics. Extreme Mechanics Letters, 71:102202. pp. 1-14. ISSN 2352-4316 (Online) (doi:https://doi.org/10.1016/j.eml.2024.102202)

convolutional neural network

Soar, Peter ORCID: 0000-0003-1745-9443 , Dall’Ara, Enrico, Palanca, Marco and Tozzi, Gianluca (2024) Data-driven image mechanics (D2IM): a deep learning approach to predict displacement and strain fields from undeformed X-ray tomography images – Evaluation of bone mechanics. Extreme Mechanics Letters, 71:102202. pp. 1-14. ISSN 2352-4316 (Online) (doi:https://doi.org/10.1016/j.eml.2024.102202)

deep learning

Soar, Peter ORCID: 0000-0003-1745-9443 , Dall’Ara, Enrico, Palanca, Marco and Tozzi, Gianluca (2024) Data-driven image mechanics (D2IM): a deep learning approach to predict displacement and strain fields from undeformed X-ray tomography images – Evaluation of bone mechanics. Extreme Mechanics Letters, 71:102202. pp. 1-14. ISSN 2352-4316 (Online) (doi:https://doi.org/10.1016/j.eml.2024.102202)

digital volume correlation

Soar, Peter ORCID: 0000-0003-1745-9443 , Dall’Ara, Enrico, Palanca, Marco and Tozzi, Gianluca (2024) Data-driven image mechanics (D2IM): a deep learning approach to predict displacement and strain fields from undeformed X-ray tomography images – Evaluation of bone mechanics. Extreme Mechanics Letters, 71:102202. pp. 1-14. ISSN 2352-4316 (Online) (doi:https://doi.org/10.1016/j.eml.2024.102202)