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. © Springer-Verlag Berlin Heidelberg 2003.
CITATION STYLE
Kim, H., Ishikawa, S., Khalid, M., Otsuka, Y., Shimizu, H., Nakada, Y., … Viergever, M. A. (2003). Automatic spinal deformity detection based on neural network. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2878, 802–809. https://doi.org/10.1007/978-3-540-39899-8_98
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