Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 7-Day Trial for You or Your Team.

Learn More →

An Approach to Unbiased Subsample Interpolation for Motion Tracking

An Approach to Unbiased Subsample Interpolation for Motion Tracking Accurate subsample displacement estimation is necessary for ultrasound elastography because of the small deformations that occur and the subsequent application of a derivative operation on local displacements. Many of the commonly used subsample estimation techniques introduce significant bias errors. This article addresses a reduced bias approach to subsample displacement estimations that consists of a two-dimensional windowed-sinc interpolation with numerical optimization. It is shown that a Welch or Lanczos window with a Nelder–Mead simplex or regular-step gradient-descent optimization is well suited for this purpose. Little improvement results from a sinc window radius greater than four data samples. The strain signal-to-noise ratio (SNR) obtained in a uniformly elastic phantom is compared with other parabolic and cosine interpolation methods; it is found that the strain SNR ratio is improved over parabolic interpolation from 11.0 to 13.6 in the axial direction and 0.7 to 1.1 in the lateral direction for an applied 1% axial deformation. The improvement was most significant for small strains and displacement tracking in the lateral direction. This approach does not rely on special properties of the image or similarity function, which is demonstrated by its effectiveness with the application of a previously described regularization technique. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Ultrasonic Imaging SAGE

An Approach to Unbiased Subsample Interpolation for Motion Tracking

McCormick, Matthew M.; Varghese, Tomy
Ultrasonic Imaging , Volume 35 (2): 14 – Apr 1, 2013
Download PDF
14 pages

Loading next page...
 
/lp/sage/an-approach-to-unbiased-subsample-interpolation-for-motion-tracking-UoUhpHNv8P

References (32)

Publisher
SAGE
Copyright
© The Author(s) 2013
ISSN
0161-7346
eISSN
1096-0910
DOI
10.1177/0161734613476176
pmid
23493609
Publisher site
See Article on Publisher Site

Abstract

Accurate subsample displacement estimation is necessary for ultrasound elastography because of the small deformations that occur and the subsequent application of a derivative operation on local displacements. Many of the commonly used subsample estimation techniques introduce significant bias errors. This article addresses a reduced bias approach to subsample displacement estimations that consists of a two-dimensional windowed-sinc interpolation with numerical optimization. It is shown that a Welch or Lanczos window with a Nelder–Mead simplex or regular-step gradient-descent optimization is well suited for this purpose. Little improvement results from a sinc window radius greater than four data samples. The strain signal-to-noise ratio (SNR) obtained in a uniformly elastic phantom is compared with other parabolic and cosine interpolation methods; it is found that the strain SNR ratio is improved over parabolic interpolation from 11.0 to 13.6 in the axial direction and 0.7 to 1.1 in the lateral direction for an applied 1% axial deformation. The improvement was most significant for small strains and displacement tracking in the lateral direction. This approach does not rely on special properties of the image or similarity function, which is demonstrated by its effectiveness with the application of a previously described regularization technique.

Journal

Ultrasonic Imaging – SAGE

Published: Apr 1, 2013

There are no references for this article.