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Image analysis techniques for characterizing disc space narrowing in cervical vertebrae interfaces.

Pavan Chamarthy·R Joe Stanley·Gregory Cizek·Rodney Long·Sameer Antani·George Thoma
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Abstract

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% for each of the four grades using a one grade window around the correct grade.

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AlgorithmsCervical VertebraeHumansImage Processing, Computer-AssistedIntervertebral DiscRadiographySpinal DiseasesJournal Article

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BibTeXRIS

Pavan Chamarthy, R Joe Stanley, Gregory Cizek, Rodney Long, Sameer Antani, George Thoma. Image analysis techniques for characterizing disc space narrowing in cervical vertebrae interfaces.. https://doi.org/10.1016/j.compmedimag.2003.10.001

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