Uniform Precision Ultrasound Strain Imaging

Departmentof Engineering, University of Cambridge, Cambridge, UK.
IEEE transactions on ultrasonics, ferroelectrics, and frequency control (Impact Factor: 1.51). 11/2009; 56(11):2420-36. DOI: 10.1109/TUFFc.2009.1330
Source: PubMed


Ultrasound strain imaging is becoming increasingly popular as a way to measure stiffness variation in soft tissue. Almost all techniques involve the estimation of a field of relative displacements between measurements of tissue undergoing different deformations. These estimates are often high resolution, but some form of smoothing is required to increase the precision, either by direct filtering or as part of the gradient estimation process. Such methods generate uniform resolution images, but strain quality typically varies considerably within each image, hence a trade-off is necessary between increasing precision in the low-quality regions and reducing resolution in the high-quality regions. We introduce a smoothing technique, developed from the nonparametric regression literature, which can avoid this trade-off by generating uniform precision images. In such an image, high resolution is retained in areas of high strain quality but sacrificed for the sake of increased precision in low-quality areas. We contrast the algorithm with other methods on simulated, phantom, and clinical data, for both 2-D and 3-D strain imaging. We also show how the technique can be efficiently implemented at real-time rates with realistic parameters on modest hardware. Uniform precision nonparametric regression promises to be a useful tool in ultrasound strain imaging.

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    • "Note that, under reasonable assumptions, SNR ρ is inversely proportional to the phase gradient variance of matching windows [8]. (4) SNR e : defined as µ s /σ s , where µ s and σ s represent respectively the mean and standard deviation within a small region of supposedly uniform strain [9]. "
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    IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control 05/2010; 57(4-57):866 - 882. DOI:10.1109/TUFFC.2010.1491 · 1.51 Impact Factor
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    ABSTRACT: This paper introduces two real-time elastography techniques based on analytic minimization (AM) of regularized cost functions. The first method (1D AM) produces axial strain and integer lateral displacement, while the second method (2D AM) produces both axial and lateral strains. The cost functions incorporate similarity of radio-frequency (RF) data intensity and displacement continuity, making both AM methods robust to small decorrelations present throughout the image. We also exploit techniques from robust statistics to make the methods resistant to large local decorrelations. We further introduce Kalman filtering for calculating the strain field from the displacement field given by the AM methods. Simulation and phantom experiments show that both methods generate strain images with high SNR, CNR and resolution. Both methods work for strains as high as 10% and run in real-time. We also present in vivo patient trials of ablation monitoring. An implementation of the 2D AM method as well as phantom and clinical RF-data can be downloaded.
    11/2010; 30(4):928-45. DOI:10.1109/TMI.2010.2091966
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