Bone Adaptation & Remodelling
Deep learning for motion grading ↗
Using convolutional neural networks to support motion-quality assessment in high-resolution bone imaging.
Published research
RESEARCH
Bone Adaptation & Remodelling
Mapping local bone formation and resorption over time, and relating these changes to the mechanical environment.
Longitudinal HR-pQCT and micro-CT let us study where bone forms and is resorbed. Combining these images with finite element models helps us examine the relationship between mechanical conditions and local tissue change.
This is the foundation of our mechanobiology work, with studies of mechanoregulation, diabetes, and recovery after spaceflight. It also underpins our open tools for registration, remodelling analysis, motion grading, and simulation.
Methods and resources
- Longitudinal image registration and tissue tracking.
- Local formation, resorption, and mechanoregulation analysis.
- Deep learning for motion grading and image segmentation.
- Image-based finite element modelling.
See our mechanoregulation study and spaceflight remodelling study.
Research highlights
Technical development
Bone Adaptation & Remodelling
Estimating loading from bone adaptation ↗
Using local tissue change and finite element models to estimate subject-specific loading in vivo.
Published research
Bone Adaptation & Remodelling
Precision of mechanoregulation measurements ↗
Establishing how reliably imaging and simulations can relate local formation and resorption to mechanical stimulus.
Published research
Mechanobiology applications
Bone Adaptation & Remodelling
Bone mechanobiology in diabetes ↗
Investigating whether bone remodelling and responsiveness to mechanical stimuli differ in type 1 diabetes.
Published research
Bone Adaptation & Remodelling
Bone adaptation after spaceflight ↗
Tracking bone loss and recovery in astronauts, through a Calgary-led programme with NASA collaborators.
Published research