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Image Analysis Techniques for Characterizing Disc Space Narrowing in Cervical Vertebrae
Image analysis techniques are introduced for evaluating disc space narrowing of cervical vertebrae interfaces from X-ray images. Four scale-invariant, distance transform-based features are presented for characterizing the spacing between adjacent vertebrae. K-means and self organizing map clustering techniques are applied to estimate the degree of disc space narrowing using a four grade (0-3) scoring system, where 0 and 3 represent normal spacing and significant narrowing, respectively. For a data set of 294 vertebrae interfaces, experimental results yield average correct grade assignment of greater than 82.10 percent for each of the four grades using a one grade window around the correct grade.