Automatic spinal deformity detection based on neural network - Kim, Hyoungseop; Ishikawa, Seiji; Khalid, Marzuki; Otsuka, Yoshinori; Shimizu, Hisashi; Nakada, Yasuhiro; Shinomiya, Takasi; Viergever, Max A. (Springer, 2003)

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We propose a technique for automatic spinal deformity detection method from moiré topographic images. Normally the moiré stripes show a symmetric pattern, as a human body is almost symmetric. According to the progress of the deformity of a spine, asymmetry becomes larger. Numerical representation of the degree of asymmetry is therefore useful in evaluating the deformity. Displacement of local centroids is evaluated statistically between the left-hand side and the right-hand side regions of the moiré images with respect to the extracted middle line. The degree of the displacement learned by a neural network employing the back propagation algorithm. An experiment was performed employing 1,200 real moiré images (600 normal and 600 abnormal) and 89% of the images were classified correctly by the NN.