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

来源：

COMPUTERIZED MEDICAL IMAGING AND GRAPHICS | 2004年 / 28卷 / 1-2期

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.

引用

页码：39 / 50

页数：12

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