DocumentCode
1143190
Title
Tendinopathy Discrimination by Use of Spatial Frequency Parameters in Ultrasound B-Mode Images
Author
Bashford, Gregory R. ; Tomsen, Nicholas ; Arya, Shruti ; Burnfield, Judith M. ; Kulig, Kornelia
Author_Institution
Univ. of Nebraska-Lincoln, Lincoln
Volume
27
Issue
5
fYear
2008
fDate
5/1/2008 12:00:00 AM
Firstpage
608
Lastpage
615
Abstract
The structural characteristics of a healthy tendon are related to the anisotropic speckle patterns observed in ultrasonic images. This speckle orientation is disrupted upon damage to the tendon structure as observed in patients with tendinopathy. Quantification of the structural appearance of tendon shows promise in creating a tool for diagnosing, prognosing, or measuring changes in tendon organization over time. The current work describes a first step taken towards this goal - classification of Achilles tendon images into tendinopathy and control categories. Eight spatial frequency parameters were extracted from regions of interest on tendon images, filtered and classified using linear discriminant analysis. Resulting algorithms had better than 80% accuracy in categorizing tendon image kernels as tendinopathy or control. Tendon images categorized wrongly provided for an interesting clinical association between incorrect classification of tendinopathy kernels as control and the symptom and clinical time history based inclusion criteria. To assess intersession reliability of image acquisition, the first 10 subjects were imaged twice during separate sessions. Test-retest of repeated measures was excellent with one outlier) indicating a general consistency in imaging techniques.
Keywords
biological tissues; biomedical ultrasonics; image classification; medical image processing; statistical analysis; Achilles tendon image classification; anisotropic speckle patterns; clinical time history; image acquisition; intersession reliability; linear discriminant analysis; spatial frequency parameter extraction; speckle orientation; tendinopathy discrimination; tendon image kernels; tendon structural characteristics; ultrasound B-mode images; Anisotropic magnetoresistance; Frequency; Kernel; Linear discriminant analysis; Nonlinear filters; Speckle; Tendons; Time measurement; Ultrasonic imaging; Ultrasonic variables measurement; Classifier; image analysis; tendinopathy; tendon; ultrasound; Algorithms; Discriminant Analysis; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Tendinopathy; Tendons; Ultrasonography;
fLanguage
English
Journal_Title
Medical Imaging, IEEE Transactions on
Publisher
ieee
ISSN
0278-0062
Type
jour
DOI
10.1109/TMI.2007.912389
Filename
4497377
Link To Document