Abstract
We propose an algorithm which processes computed tomography images of vertebral bodies, segments them into the areas of interest and then quantifies their structure using approaches developed in nonlinear dynamics. Vertebral bodies are segmented from the connective and soft tissue background, and then the image of the entire vertebrae are split into the cortical and trabecular bones. At the next stage, several criteria, based on nonlinear dynamics, complexity measures and symbolic dynamics, are applied. We show that these measures indeed contribute significantly to the early diagnostics of changes in bone structure, which are specific for osteoporosis and other bone diseases.
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