A Noncontact, Nondestructive Method for Quantifying Intratissue Deformations and Strains

[+] Author and Article Information
M. J. Bey

Department of Biomedical Engineering, University of Cincinnati, 840 Engineering Research Center, Cincinnati, OH 45221

H. K. Song, F. W. Wehrli

Department of Radiology, University of Pennsylvania, 1 Silverstein/MRI, 3400 Spruce Street, Philadelphia, PA 19104

L. J. Soslowsky

McKay Orthopaedic Research Laboratory, University of Pennsylvania, 424 Stemmler Hall, Philadelphia, PA 19104

J Biomech Eng 124(2), 253-258 (Mar 29, 2002) (6 pages) doi:10.1115/1.1449917 History: Received October 17, 2000; Revised October 08, 2001; Online March 29, 2002
Copyright © 2002 by ASME
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Grahic Jump Location
Original grid of nodal points superimposed on a representative MR image. This particular image is a scapular plane section through a cadaveric shoulder specimen. Each nodal point represents the center of a small region of the image. These individual regions are treated as unique markers and are used as inputs to the texture correlation’s pattern-matching algorithm. SP=supraspinatus tendon, HH=humeral head.
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Test images with Gaussian-distributed noise superimposed on the original image. These images have a SNR of 13.0 (left) and 3.8 (right) in the tendon.
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MRI-compatible displacement accuracy testing fixture and corresponding MR image. The cylindrical reservoirs were filled with copper sulfate to provide sufficient MR signal.
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Schematic of the testing chamber used for comparing the accuracy of texture correlation with optical techniques. The MR image plane was oriented parallel to the sponge’s visible surface.
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Average radial error when applying the texture correlation analysis to MR images with one-dimensional (1d) and two-dimensional (2d) simulated displacements
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Texture correlation measurements of simulated subpixel displacements. The graph shows the effect of zero (int0), one (int1), and two (int2) interpolations of the input images. Each interpolation increases the image resolution (i.e., decreases the pixel size by a factor of two), and decreases the measurement uncertainty by a factor of two.
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Comparison of average (±standard deviation) compressive strain for the MRI and optical-based approaches (n=60 nodal points). There was no significant difference in average compressive strain. Representative optical (A) and MR (B) images are also shown.



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