5 research outputs found

    Prediction of bone microstructures degradation during osteoporosis with fuzzy cellular automata algorithm

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    A novel fuzzy cellular automata is proposed to simulate bone degradation during osteoporosis. The initial three-dimensional (3D) bone microstructure is obtained from computed tomography (CT) images. Cellular automata algorithm is implemented to the 3D lattice and a Sugeno Fuzzy inference system is designed with nine sets of fuzzy rules to simulate the degradation process. A distance vector parameter is defined to describe the number of neighborhood cells that each cell can have a connection with. It is shown that by increasing the value of this distance vector, the results converge toward a quasi-constant degraded microstructure. The obtained microstructure is considered to be the final result and compared to prediction of bone degradation of the literature based on phase exchange calculated from mechanical strain energy. It is shown that the fuzzy cellular automata model predicts a more realistic bone degradation and microstructure distribution than the phase exchange method while having a model significantly simpler
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