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Automatic spinal deformity detection based on neural network

Kim, Hyoungseop and Ishikawa, Seiji and Khalid, Marzuki and Otsuka, Yoshinori and Shimizu, Hisashi and Nakada, Yasuhiro and Shinomiya, Takasi and Viergever, Max A. (2003) Automatic spinal deformity detection based on neural network. In: Medical Image Computing and Computer-Assisted Intervention. Lecture Notes in Computer Science, 2878 . Springer, Verlag Berlin Heidelberg, pp. 802-809. ISBN 978-3-540-20462-6

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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.

Item Type:Book Section
Uncontrolled Keywords:automatic spinal, topographic images
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computer Science and Information System
ID Code:7146
Deposited By: Surayahani Abu Bakar
Deposited On:20 Jan 2009 08:41
Last Modified:25 Jul 2017 04:11

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