Novel spline-based approach for robust strain estimation in elastography.
Robust strain estimation is important in elastography. However, a high signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) are sometimes attained by sacrificing resolution. We propose a least-squares-based smoothing-spline strain estimator that can produce elastograms with high SNR and CNR without significant loss of resolution. The proposed method improves strain-estimation quality by deemphasing displacements with lower correlation in computing strains. Results from finite-element simulation and phantom-experiment data demonstrate that the described strain estimator provides good SNR and CNR without degrading resolution.
Alam
S Kaisar
SK
Riverside Research Institute, 156 William Street, New York, NY 10038, USA. kalam@rri-usa.org
D000162:Acoustics; D000465:Algorithms; D003198:Computer Simulation; D054459:Elasticity Imaging Techniques / Q000379:methods*; D007089:Image Enhancement / Q000379:methods; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D016018:Least-Squares Analysis; D019047:Phantoms, Imaging; D012815:Signal Processing, Computer-Assisted