Correction of tissue-motion effects on common-midpoint signals using reciprocal signals.

Information and Communication Technologies Centre, Commonwealth Scientific and Industrial Research Organisation, Marsfield, New South Wales 2122, Australia.
The Journal of the Acoustical Society of America (Impact Factor: 1.65). 08/2012; 132(2):872-82. DOI: 10.1121/1.4730913
Source: PubMed

ABSTRACT The near field signal redundancy algorithm for phase-aberration correction is sensitive to tissue motion because several separated transmissions are usually needed to acquire a set of common-midpoint signals. If tissues are moving significantly due to, for example, heart beats, the effects of tissue motion on common-midpoint signals need to be corrected before the phase-aberration profile can be successfully measured. Theoretical analyses in this paper show that the arrival-time difference between a pair of common-midpoint signals due to tissue motion is usually very similar to that between the pair of reciprocal signals acquired using the same two transmissions. Based on this conclusion, an algorithm for correcting tissue-motion effects on the peak position of cross-correlation functions between common-midpoint signals is proposed and initial experimental results are also presented.

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: A method for estimating waveform aberration from random scatterers in medical ultrasound imaging has been derived and its properties investigated using two-dimensional simulations. The method uses a weighted and modified cross-spectrum in order to estimate arrival time and amplitude fluctuations from received signals. The arrival time and amplitude fluctuations were used in a time delay, and a time delay and amplitude aberration correction filter, for evaluation of the retransmitted aberration corrected signal. Different types of aberration have been used in this study. First, aberration was concentrated on the plane of the transmitting/receiving array. Second, aberration was generated with a distributed aberrator. Both conditions emulated aberration from the human abdominal wall. Results show that for the concentrated aberrator, arrival time and amplitude fluctuations were estimated in close agreement with reference values. The reference values were obtained from simulations with a point source in the focal point of the array. Correction of the transmitted signal with a time delay, and a time delay and amplitude filter produced approximately equal correction as with point source estimates. For the distributed aberrator, the estimator performance degraded significantly. Arrival time and amplitude fluctuations deviated from reference values, leading to a limited correction of the retransmitted signal.
    The Journal of the Acoustical Society of America 07/2004; 115(6):2998-3009. · 1.56 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: As medical ultrasound imaging moves to larger apertures and higher frequencies, tissue sound-speed variations continue to limit resolution. In geophysical imaging, a standard approach for estimating near-surface aberrating delays is to analyze the time shifts between common-midpoint signals. This requires complete data-echoes from every source/receiver pair in the array. Unfocused common-midpoint signals remain highly correlated in the presence of delay aberrations; there is also tremendous redundancy in the data. In medical ultrasound, this technique has been impaired by the wide-angle, random-scattering nature of tissue. This has made it difficult to estimate azimuth-dependent aberration profiles or to harness the full redundancy in the complete data. Prefiltering the data with two-dimensional fan filters mitigates these problems, permitting highly overdetermined, least-squares solutions for the aberration profiles at many steering angles. In experiments with a tissue-mimicking phantom target and silicone rubber aberrators at nonzero stand-off distances from a one-dimensional phased array, this overdetermined, fan-filtering algorithm significantly outperformed other phase-screen algorithms based on nearest-neighbor cross-correlation, speckle brightness maximization, and common-midpoint signal analysis. Our results imply that there is still progress to be made in imaging with single-valued focusing operators. It also appears that the signal-to-noise penalty for using complete data sets is partially compensated by the overdetermined nature of the problem.
    IEEE Transactions on Medical Imaging 11/2004; 23(10):1205-20. · 3.80 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: An inverse scattering method that uses eigenfunctions of the scattering operator is presented. This approach provides a unified framework that encompasses eigenfunction methods of focusing and quantitative image reconstruction in arbitrary media. Scattered acoustic fields are described using a compact, normal operator. The eigenfunctions of this operator are shown to correspond to the far-field patterns of source distributions that are directly proportional to the position-dependent contrast of a scattering object. Conversely, the eigenfunctions of the scattering operator specify incident-wave patterns that focus on these effective source distributions. These focusing properties are employed in a new inverse scattering method that represents unknown scattering media using products of numerically calculated fields of eigenfunctions. A regularized solution to the nonlinear inverse scattering problem is shown to result from combinations of these products, so that the products comprise a natural basis for efficient and accurate reconstructions of unknown inhomogeneities. The corresponding linearized problem is solved analytically, resulting in a simple formula for the low-pass-filtered scattering potential. The linear formula is analytically equivalent to known filtered-backpropagation formulas for Born inversion, and, at least in the case of small scattering objects, has advantages of computational simplicity and efficiency. A similarly efficient and simple formula is derived for the nonlinear problem in which the total acoustic pressure can be determined based on an estimate of the medium. Computational results illustrate focusing of eigenfunctions on discrete and distributed scattering media, quantitative imaging of inhomogeneous media using products of retransmitted eigenfunctions, inverse scattering in an inhomogeneous background medium, and reconstructions for data corrupted by noise.
    The Journal of the Acoustical Society of America 09/1997; 102(2 Pt 1):715-25. · 1.56 Impact Factor