2018
DOI: 10.1109/tuffc.2018.2828644
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Ultrasonic Wave-Speed Diffraction Tomography With Undersampled Data Using Virtual Transducers

Abstract: Ultrasonic diffraction tomography offers a way to achieve high-resolution imaging of the wave-speed map, and hence, has strong potential applications in medical diagnosis and nondestructive evaluation. Ideal images can be obtained with a complete array of sensors surrounding the scatterer, provided that the measurement data are fully sampled in space, obeying the Nyquist criterion. Spatial undersampling causes the image to be distorted and introduce unwanted circular artifacts. In this paper, we propose an ite… Show more

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Cited by 9 publications
(3 citation statements)
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“…Deal and Nolet [33] used a 'null space shuttle' to seismic tomographic problems where a non-linear filter is estimated and applied as a post processing step and only modifies components of the null space. Huthwaite et al [34] and Shi and Huthwaite [35] applied an iterative null space regularization method to limited view ultrasonic imaging, applying a threshold to the image from the previous iteration. This threshold image is used to generate synthetic data for the missing viewing angles which are incorporated with the measured data to perform the next iteration of the procedure.…”
Section: Null Space Regularizationmentioning
confidence: 99%
See 1 more Smart Citation
“…Deal and Nolet [33] used a 'null space shuttle' to seismic tomographic problems where a non-linear filter is estimated and applied as a post processing step and only modifies components of the null space. Huthwaite et al [34] and Shi and Huthwaite [35] applied an iterative null space regularization method to limited view ultrasonic imaging, applying a threshold to the image from the previous iteration. This threshold image is used to generate synthetic data for the missing viewing angles which are incorporated with the measured data to perform the next iteration of the procedure.…”
Section: Null Space Regularizationmentioning
confidence: 99%
“…Here, we apply a similar strategy to [34] and [35], but specifically tailored it to limited data x-ray CT. Below we review the theory used by [34] and [35] for ultrasonic imaging. As stated previously the main objective of any imaging approach is to reconstruct an image x, from a set of measurements d by undoing the linear operator L. However, L is not invertible in general, since there are multiple sets of x which can produce the same data d. We define a corresponding imaging operator I which can therefore only generate x , an approximation of x,…”
Section: Null Space Regularizationmentioning
confidence: 99%
“…However, increasing the number of sensors has a cost, particularly in terms of intrusiveness. A response to that issue could be to use undersampled data (Druet et al, 2019;Shi and Huthwaite, 2018) but, for now, the number of sensors' reduction achieved is of a factor two to four with respect to the optimal number. This reduction seems to be not enough for some industrial sectors such as aeronautic industry which has a tremendous added mass constrain.…”
Section: Introductionmentioning
confidence: 99%