Acoustical image reconstruction in parallel-processing analog electronic systems

Delannoy, B.; Torguet, R.; Bruneel, C.; Bridoux, E.; Rouvaen, J.M.; Lasota, H.

doi:10.1063/1.326397

Cited by 67 publications

(48 citation statements)

References 3 publications

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“…Then (1) can be rewritten as (2) where f, s and n are the vector versions of f(k), s(k), n(k), and n(k), respectively. The imaging operator G, defined as (3) is a (typically, underdetermined) matrix operator consisting of N φ linear convolution matrices. Thus, a unique minimum-norm least-square estimate (denoted by ŝ below) of the scatterer vector s can be expressed as (4) where PIO is a pseudoinverse operator [17], [25] equal to (5) The superscripts * , t , and † represent conjugate, transpose, and generalized inverse operators, respectively.…”

Section: A System Modelmentioning

confidence: 99%

“…Recent progress in transducer fabrication and very-large-scale integration signal processing have motivated several research groups to pursue high-speed ultrasound pulse-echo imaging systems capable of parallel processing multiple image lines for real-time 3-D imaging applications [3], [18], [23], [24], [26], [31], [33], [35]. Basically, two approaches have been proposed and investigated for realizing parallel image line processing.…”

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confidence: 99%

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Filter-based coded-excitation system for high-speed ultrasonic imaging

Shen

Ebbini

1998

IEEE Trans. Med. Imaging

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We have recently presented a new algorithm for high-speed parallel processing of ultrasound pulse-echo data for real-time three-dimensional (3-D) imaging. The approach utilizes a discretized linear model of the echo data received from the region of interest (ROI) using a conventional beam former. The transmitter array elements are fed with binary codes designed to produce distinct impulse responses from different directions in ROI. Image reconstruction in ROI is achieved with a regularized pseudoinverse operator derived from the linear receive signal model. The reconstruction operator can be implemented using a transversal filter bank with every filter in the bank designed to extract echoes from a specific direction in the ROI. The number of filters in the bank determines the number of image lines acquired simultaneously. In this paper, we present images of a cyst phantom reconstructed based on our formulation. A number of issues of practical significance in image reconstruction are addressed. Specifically, an augmented model is introduced to account for imperfect blocking of echoes from outside the ROI. We have also introduced a column-weighting algorithm for minimizing the number of filter coefficients. In addition, a detailed illustration of a full image reconstruction using subimage acquisition and compounding is given. Experimental results have shown that the new approach is valid for phased-array pulse-echo imaging of speckle-generating phantoms typically used in characterizing medical imaging systems. Such coded-excitation-based image reconstruction from specklegenerating phantoms, to the best of our knowledge, have not been reported previously.

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Section: A System Modelmentioning

confidence: 99%

mentioning

confidence: 99%

Filter-based coded-excitation system for high-speed ultrasonic imaging

Shen

Ebbini

1998

IEEE Trans. Med. Imaging

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“…where we have used (11) in the last equality. Thus the LMMSE estimator reduces to a matched filter, P T y, when the noise is large (which has the well-known property to optimize the SNR at a single point).…”

Section: Sensitivity To the Snr Settingmentioning

confidence: 99%

“…If many points could be reconstructed from a single transmission, then the frame rate could be increased significantly. Such systems have been proposed before where a wider-than-normal transmit beam is used and a few lines of the total ROI are reconstructed using a parallel receive beamformer [11]- [13]. These systems can, however, beamform only a few lines per transmission.…”

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confidence: 99%

On Time-Domain Model-Based Ultrasonic Array Imaging

Lingvall

Olofsson

2007

IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

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Abstract-This paper treats time-domain model-basedBayesian image reconstruction for ultrasonic array imaging and, in particular, two reconstruction methods are presented. These two methods are based on a linear model of the array imaging system and they perform compensation in both the spatial and temporal domains using a minimum mean squared error (MMSE) criterion and a maximum a posteriori MAP) estimation approach, respectively. The presented estimators perform compensation for both the electrical and acoustical wave propagation effects for the ultrasonic array system at hand. The estimators also take uncertainties into account, and, by the incorporation of proper prior knowledge, high-contrast superresolution reconstruction results are obtained. The novel nonlinear MAP estimator constrains the scattering amplitudes to be positive, which applies in applications where the scatterers have higher acoustic impedance than the surrounding medium. The linear MMSE and nonlinear MAP estimators are compared to the traditional delay-and-sum (DAS) beamformer with respect to both resolution and signal-tonoise ratio. The algorithms are compared using both simulated and measured data. The results show that the modelbased methods can successfully compensate for both sidelobes and grating lobes, and they have a superior temporal and lateral resolution compared to DAS beamforming. The ability of the nonlinear MAP estimator to suppress noise is also superior compared to both the linear MMSE estimator and the DAS beamformer.

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“…It was first developed and examined in the 1970s [1][2][3]. In ultrafast ultrasound imaging, unfocused transmit beams, such as plane and diverging beams, are used.…”

Section: Ultrafast Ultrasound Imagingmentioning

confidence: 99%