ArticleFrontiers in bioengineering and biotechnology2022
Designing anisotropic porous bone scaffolds using a self-learning convolutional neural network model.
Article in Frontiers in bioengineering and biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Extending the Discussion on Bioengineered Tooth Regeneration: Translational Considerations for Clinical Implementation.Annals of biomedical engineering · 2026Article
- Design and Fabrication of Biomimetic Gradient Bone Tissue Engineering Scaffolds: Evolution from Single-Gradient to Multi-Gradient.Gels (Basel, Switzerland) · 2026Review
- AI-driven 3D bioprinting for regenerative medicine: From bench to bedside.Bioactive materials · 2025Review
- A Novel Triad of Bio-Inspired Design, Digital Fabrication, and Bio-Derived Materials for Personalised Bone Repair.Materials (Basel, Switzerland) · 2024Review
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6 authors.
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Abstract
The design of bionic bone scaffolds to mimic the behaviors of native bone tissue is crucial in clinical application, but such design is very challenging due to the complex behaviors of native bone tissues. In the present study, bionic bone scaffolds with the anisotropic mechanical properties similar to those of native bone tissues were successfully designed using a novel self-learning convolutional neural network (CNN) framework. The anisotropic mechanical property of bone was first calculated from the CT images of bone tissues. The CNN model constructed was trained and validated using the predictions from the heterogonous finite element (FE) models. The CNN model was then used to design the scaffold with the elasticity matrix matched to that of the replaced bone tissues. For the comparison, the bone scaffold was also designed using the conventional method. The results showed that the mechanical properties of scaffolds designed using the CNN model are closer to those of native bone tissues. In conclusion, the self-learning CNN framework can be used to design the anisotropic bone scaffolds and has a great potential in the clinical application.
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