Statistical shape and appearance models in osteoporosis
Isaac Castro-Mateos1, Jose M Pozo, Timothy F Cootes
1Center for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), Mechanical Engineering Department, The University of Sheffield, Sheffield, UK, isaac.casm@sheff.ac.uk.
Abstract:
Statistical models (SMs) of shape (SSM) and appearance (SAM) have been acquiring popularity in medical image analysis since they were introduced in the early 1990s. They have been primarily used for segmentation, but they are also a powerful tool for 3D reconstruction and classification. All these tasks may be required in the osteoporosis domain, where fracture detection and risk estimation are key to reducing the mortality and/or morbidity of this bone disease. In this article, we review the different applications of SSMs and SAMs in the context of osteoporosis, and it concludes with a discussion of their advantages and disadvantages for this application.
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