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Prediction of scoliosis curve type based on the analysis of trunk surface topography
Is part ofBiomedical Imaging, IEEE International Symposium on; Biomedical Imaging: From Nano to Macro, 2010.
- Université de Montréal. Faculté de médecine. Département de chirurgie
Scoliosis treatment strategy is generally chosen according to the severity and type of the spinal curve. Currently, the curve type is determined from X-rays whose acquisition can be harmful for the patient. We propose in this paper a system that can predict the scoliosis curve type based on the analysis of the surface of the trunk. The latter is acquired and reconstructed in 3D using a non invasive multi-head digitizing system. The deformity is described by the back surface rotation, measured on several cross-sections of the trunk. A classifier composed of three support vector machines was trained and tested using the data of 97 patients with scoliosis. A prediction rate of 72.2% was obtained, showing that the use of the trunk surface for a high-level scoliosis classification is feasible and promising.
Seoud L, Adankon MM, Labelle H, Dansereau J, Cheriet, F. Prediction of scoliosis curve type based on the analysis of trunk surface topography. Dans: 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro; 14-17 avr 2010; Rotterdam, Pays-bas. Piscataway (NJ): IEEE; 2010. p. 408-411.