Understanding bone structure evolution using machine learning

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Bone remodeling is the ancient process of bone resorption and formation that optimises material properties and has led to evolution of terrestrial vertebrates. To date it is not understood how remodeling achieves tuning of bone material. This proposal aims to develop a machine learning based approach, linking computational modeling and imaging to address this problem. Intended outcomes are development of a multiscale model of remodeling and machine learning algorithms for image analysis. This approach will help establish a structural-functional link between remodeling and bone material optimisation which ultimately provides significant benefits for bone tissue engineering, fracture healing and improved therapies for osteoporosis.