A Dictionary Learning-Based Fast Imaging Method for Ultrasound Elastography
Ultrasound elastography is an imaging modality that computes the elasticity of tissue through measuring shear waves from a mechanical excitation using pulse-echo ultrasound. To better measure shear waves and reduce acquisition time, elastography would benefit from a higher framerate, which is limited by conventional focused line-by-line acquisition. This paper proposes a dictionary learning-based framework that increases the framerate of steady state elastography. The method uses patches extracted from images with higher scanline density to train a dictionary, and uses this dictionary to interpolate images with lower scanline density collected at a faster framerate. Experiments on a tissue mimicking phantom showed when the framerate is increased 8 times, the reconstructed image using the proposed method achieved a 17.6 dB Peak Signal-to-Noise Ratio. The method was also implemented on a steady state elastography system, where elasticity measurements similar to conventional methods were obtained with a shorter total acquisition time.
KeywordsDictionary learning Fast imaging Ultrasound elastography
This work was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Canadian Institutes of Health Research (CIHR). We thank Drs. Mohammad Honarvar and Julio Lobo for engineering help with SWAVE.
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