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Proceedings Paper

Scoliosis curve type classification using kernel machine from 3D trunk image
Author(s): Mathias M. Adankon; Jean Dansereau; Stefan Parent; Hubert Labelle; Farida Cheriet
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Paper Abstract

Adolescent idiopathic scoliosis (AIS) is a deformity of the spine manifested by asymmetry and deformities of the external surface of the trunk. Classification of scoliosis deformities according to curve type is used to plan management of scoliosis patients. Currently, scoliosis curve type is determined based on X-ray exam. However, cumulative exposure to X-rays radiation significantly increases the risk for certain cancer. In this paper, we propose a robust system that can classify the scoliosis curve type from non invasive acquisition of 3D trunk surface of the patients. The 3D image of the trunk is divided into patches and local geometric descriptors characterizing the surface of the back are computed from each patch and forming the features. We perform the reduction of the dimensionality by using Principal Component Analysis and 53 components were retained. In this work a multi-class classifier is built with Least-squares support vector machine (LS-SVM) which is a kernel classifier. For this study, a new kernel was designed in order to achieve a robust classifier in comparison with polynomial and Gaussian kernel. The proposed system was validated using data of 103 patients with different scoliosis curve types diagnosed and classified by an orthopedic surgeon from the X-ray images. The average rate of successful classification was 93.3% with a better rate of prediction for the major thoracic and lumbar/thoracolumbar types.

Paper Details

Date Published: 23 February 2012
PDF: 7 pages
Proc. SPIE 8315, Medical Imaging 2012: Computer-Aided Diagnosis, 831514 (23 February 2012); doi: 10.1117/12.911335
Show Author Affiliations
Mathias M. Adankon, Ecole Polytechnique de Montréal (Canada)
Sainte-Justine Hospital Research Ctr. (Canada)
Jean Dansereau, Ecole Polytechnique de Montréal (Canada)
Sainte-Justine Hospital Research Ctr. (Canada)
Stefan Parent, Sainte-Justine Hospital Research Ctr. (Canada)
Hubert Labelle, Sainte-Justine Hospital Research Ctr. (Canada)
Farida Cheriet, Ecole Polytechnique de Montréal (Canada)
Sainte-Justine Hospital Research Ctr. (Canada)

Published in SPIE Proceedings Vol. 8315:
Medical Imaging 2012: Computer-Aided Diagnosis
Bram van Ginneken; Carol L. Novak, Editor(s)

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