Automatic spinal deformity detection based on neural network

Automatic spinal deformity detection based on neural network

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...

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Bibliographic Details
Main Authors: Kim, Hyoungseop, Ishikawa, Seiji, Khalid, Marzuki, Otsuka, Yoshinori, Shimizu, Hisashi, Nakada, Yasuhiro, Shinomiya, Takasi, Viergever, Max A.
Other Authors: Ellis, R.E.
Format: Book Section
Published: Springer 2003
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://eprints.utm.my/7146/
Description
Summary: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.

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