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A support vector machines (SVM) classifier was used to assess the severity of idiopathic scoliosis (IS) based on surface topographic images of human backs. Scoliosis is a condition that involves abnormal lateral curvature and rotation of the spine that usually causes noticeable trunk deformities. Based on the hypothesis that combining surface topography and clinical data using a SVM would produce better assessment results, we conducted a study using a dataset of 111 IS patients. Twelve surface and clinical indicators were obtained for each patient. The result of testing on the dataset showed that the system achieved 69-85% accuracy in testing. It outperformed a linear discriminant function classifier and a decision tree classifier on the dataset.

Osteoarthritis is a debilitating joint disease where the articular cartilage surface degrades and is unable to repair itself through natural processes. Chondrocytes reside within the cartilage matrix and maintain its structure. We conducted in vitro experiments to investigate the morphological response of cultured human chondrocytes under different pulsed electromagnetic field (PEMF) conditions. In the control experiments, cultured chondrocytes attached to the bottom of a culture dish typically displayed either a stellate or spindle morphology with extended processes. Experimental chondrocyte cultures were placed in a Helmholtz coil to which a ramp waveform was applied. Exposure to PEMFs caused the chondrocytes to retract their processes, becoming spherical in shape. This change in morphology followed a progression from stellate to spindle to spherical. These morphological changes were reflected in an average reduction of 30% in the surface contact area of the chondrocytes to the culture dish. Understanding the mechanisms by which PEMFs affect the morphology of chondrocytes will help lead to new treatments for osteoarthritis.

Analysis of three-dimensional (3D) images of human torsos for torso deformities such as scoliosis requires classifying torso distortion. Assessing torso distortion from 3D images is not trivial as actual torsos are non-symmetric and show an outstanding range of variations leading to high classification errors. As the degree of spinal deformity (and classification of torso shape) influences scoliosis treatment options, the development of more accurate classification procedures is desirable. This paper presents a technique for assessing torso shape and classifying scoliosis into mild, moderate and severe categories using two indices, 'twist' and 'bend', obtained from orthogonally transformed images of the complete torso surface called orthogonal maps. Four transforms (axial line, unfolded cylinder, enclosing cylinder and subtracting cylinder) were used. Blind tests on 361 computer models with known deformation parameter values show 100% classification accuracy. Tests on eight volunteers without scoliosis validated the system and tests on 22 torso images of volunteers with scoliosis showed up to 95.5% classification accuracy. In addition to classifying scoliosis, orthogonal maps present the entire torso in one view and are viable for use in scoliosis clinics for monitoring the progression of scoliosis.

The efficacy of orthotic treatment for children with abnormal spinal curvature has been hampered by the lack of comprehensive information about wear characteristics.

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Trunk images of children with scoliosis were examined to determine features that contribute to the impression of trunk distortion. Twenty subjects with spinal deformity ranging from none to severe were photographed in a relaxed standing position. Seven blinded evaluators subjectively scored their impressions of the trunk appearance, shoulder-height difference, shoulder-angle asymmetry, decompensation, scapula asymmetry, waist crease, waist asymmetry, and pelvic asymmetry. Regression analysis was used with the latter seven features to predict overall impression. The seven measures of the deformity predicted 85% of the overall impression of trunk distortion; scapular asymmetry was the best predictor. Trunk deformity is the most obvious effect of scoliosis to the patients. Objective approaches to the assessment of this important but difficult-to-quantify aspect of idiopathic scoliosis are available and should be used to evaluate treatment outcomes.