A least-squares strain estimator for elastography.
A least-squares strain estimator (LSQSE) for elastography is proposed. It is shown that with such an estimator, the signal-to-noise ratio in an elastogram (SNRe) is significantly improved. This improvement is illustrated theoretically using a modified strain filter and experimentally using a homogeneous gel phantom. It is demonstrated that the LSQSE results in an increase of the elastographic sensitivity (smallest, strain that could be detected), thereby increasing the strain dynamic range. Using simulated data, it is shown that a tradeoff exists between the improvement in SNRe and the reduction of strain contrast and spatial resolution.
Kallel
F
F
University of Texas Medical School, Department of Radiology, Houston 77030, USA.
Ophir
J
J
D003238:Connective Tissue / Q000000981:diagnostic imaging*; D004548:Elasticity; D005374:Filtration; D006801:Humans; D016018:Least-Squares Analysis; D008954:Models, Biological; D015233:Models, Statistical; D019047:Phantoms, Imaging; D012815:Signal Processing, Computer-Assisted; D014463:Ultrasonography