Automatic Judgement of Spinal Deformity from Moire Images Employing Asymmetry of Local Centroids Location

A technique is described for classifying abnormal cases and normal cases in automatic spinal deformity analysis by computer based on moire topographic images of human backs. Displacement of local centroids is evaluated statistically between the left-hand side and the right-hand side of the moire images. The technique was applied to real subjects images in order to draw a distinction between 60 normal and 60 abnormal cases. According to the leave-out method, the entire data was separated into three sets. The linear discriminant function based on the Mahalanobis distance was defined on the 2-D feature space employing one of the data sets containing 40 moire images and classified 80 images in the remaining two sets. The average classification rate was 87.9%.