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Image analysis techniques for characterizing disc space narrowing in cervical vertebrae interfaces
被引:14
|作者:
Chamarthy, P
Stanley, RJ
[1
]
Cizek, G
Long, R
Antani, S
Thoma, G
机构:
[1] Univ Missouri, Dept Elect & Comp Engn, Rolla, MO 65409 USA
[2] Excel Imaging, St Louis, MO USA
[3] Natl Lib Med, Commun Engn Branch, Bethesda, MD USA
关键词:
degenerative disk disease;
disc space narrowing;
image processing;
cervical spine disorders;
K-means;
self-organizing maps;
D O I:
10.1016/j.compmedimag.2003.10.001
中图分类号:
R318 [生物医学工程];
学科分类号:
0831 ;
摘要:
Image analysis techniques are introduced for evaluating disc space narrowing of cervical vertebrae interfaces from X-ray images. Four scale-invariant, distance transforrn-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. (C) 2003 Elsevier Ltd. All rights reserved.
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页码:39 / 50
页数:12
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