PubMed · 7473355
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B Lepage, P Dariane. 1995. [Echography].. https://pubmed.ncbi.nlm.nih.gov/7473355/
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Two-dimensional arrays are necessary for a variety of ultrasonic imaging techniques, including elevation focusing, 2-D phase aberration correction, and real time volumetric imaging. In order to reduce system cost and complexity, sparse 2-D arrays have been considered with element geometries selected ad hoc, by algorithm, or by random process. Two random sparse array geometries and a sparse array with a Mills cross receive pattern were simulated and compared to a fully sampled aperture with the same overall dimensions. The sparse arrays were designed to the constraints of the Duke University real time volumetric imaging system, which employs a wide transmit beam and receive mode parallel processing to increase image frame rate. Depth-of-field comparisons were made from simulated on-axis and off-axis beamplots at ranges from 30 to 160 mm for both coaxial and offset transmit and receive beams. A random array with Gaussian distribution of transmitters and uniform distribution of receivers was found to have better resolution and depth-of-field than both a Mills cross array and a random array with uniform distribution of both transmit and receive elements. The Gaussian random array was constructed and experimental system response measurements were made at several ranges. Comparisons of B-scan images of a tissue mimicking phantom show improvement in resolution and depth-of-field consistent with simulation results.
Very large, two-dimensional, anisotropic arrays have been proposed to improve ultrasound image quality. Due to noncontiguous acoustic windows into the body, however, a significant portion of such an aperture may be blocked. Blocked elements result in high sidelobes in the point spread function, degrading image quality. To compensate for this, an object dependent method using multiple receive beams has been recently proposed. This method is effective in removing undesired sidelobes. However, previous results were for one-dimensional arrays where only lateral beams were used for estimation. With two-dimensional arrays, the distribution of blocked elements can change beam characteristics, both laterally and elevationally. In other words, receive beams must be formed in both directions for better performance. Although straightforward in principle, extension of the algorithm from one dimension to two increases computational complexity dramatically. Furthermore, the restricted elevational steering capability of anisotropic arrays also limits performance. In this paper, several computationally efficient algorithms for two-dimensional blocked element compensation are proposed and evaluated. It is shown that undesired sidelobes can be effectively removed using only a limited number of receive beams. Image quality can therefore be restored in the presence of blocked elements without significantly increasing hardware complexity.
An algorithm for the estimation of one-dimensional in-vivo ultrasound pulses is derived. The routine estimates a set of ARMA parameters describing the pulse and uses data from a number of adjacent rf lines. Using multiple lines results in a decrease in variance on the estimated parameters and significantly reduces the risk of terminating the algorithm at a local minimum. Examples from use on synthetic data confirms the reduction in variance and increased chance of successful minimization termination. Simulations are also reported indicating the relation between the one-dimensional pulse and the three-dimensional, attenuated ultrasoud field for a concave transducer. Pulses are estimated from in-vivo liver data showing good resemblance to a pulse measured as the response from a planar reflector and then properly attenuated. The main application for the algorithm is to function as a preprocessing stage for deconvolution algorithms using parametric pulses.