Title

Image Analysis Techniques for Characterizing Disc Space Narrowing in Cervical Vertebrae Interfaces

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.

Department(s)

Electrical and Computer Engineering

Keywords and Phrases

K-Means; Cervical Spine Disorders; Degenerative Disk Disease; Disc Space Narrowing; Image Processing

Library of Congress Subject Headings

Cervical vertebrae
Self-organizing maps

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2004 Elsevier, All rights reserved.


Share

 
COinS