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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Conflict of Interest
I. Castro-Mateos. J. M. Pozo, J. M. Wilkinson and A. F. Frangi declare that they have no conflicts of interest. T. F. Cootes has begun to collaborate with Optasia-Medical Ltd to develop an automated system for identifying vertebral fractures (funded by MRC and the Wellcome Trust). R Eastell has received grants from Amgen, Department of Health, AstraZeneca, Immunodiagnostic Systems, Canadian Institutes of Health Research, National Osteoporosis Society, ARUK/MRC Centre of Excellence in Musculoskeletal Ageing Research, National Institute for Health Research, Cancer Research UK, MRC/AZ Mechanisms of Diseases Call; personal fees from Novartis, Roche, Alexion, Otsuka, Merck, Johnson & Johnson, SPD Development, Fonterra Brands, Janssen Research, Eli Lilly, Ono Pharma, Immunodiagnostic Systems, Alere (Unipath), Chronos, Amgen, IBMS; is on an advisory board for European Calcified Tissue Society, Efficacy & Mechanism Evaluation Board of the Medical Research Council, Eli Lilly, Roche, IOF CSA outside the submitted work.
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All studies by the authors involving animal and/or human subjects were performed after approval by the appropriate institutional review boards.When required, written informed consent was obtained from all participants.
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Castro-Mateos, I., Pozo, J.M., Cootes, T.F. et al. Statistical Shape and Appearance Models in Osteoporosis. Curr Osteoporos Rep 12, 163–173 (2014). https://doi.org/10.1007/s11914-014-0206-3
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DOI: https://doi.org/10.1007/s11914-014-0206-3