Ultrasound imaging using variations of the iterative Born technique [biomedical diagnosis]

The iterative Born method is an inverse technique that has been used successfully in ultrasound imaging. However, the calculation cost of the standard iterative Born method is high, and parallel computation is limited to the forward problem. In this work, two methods are introduced to increase the rate of convergence of the iterative Born algorithm. These methods are tested on three different objects. The results are promising, with both algorithms giving accurate results at lower computational cost. The first method, referred to as the coarse resolution initial value (CRIV) method, uses the iterative Born algorithm for a coarse grid to quickly estimate the initial value of the object to be reconstructed. From this initial value, the final image is obtained for a finer grid with additional iterations. The cost of this method is 40% less than that of the iterative Born technique. The second method, the quadriphase source (QS) method, simultaneously uses four single sources, and object reconstruction for each is performed in parallel; the reconstruction results for all four sources then are averaged to obtain the final image. The cost of this method is 20% less than that of the standard iterative Born method. When the object to be reconstructed is of low contrast and/or has a small phase shift, the QS method is very promising because parallel computation can be used to solve both the forward and inverse problems. However, the QS method fails for high contrast objects.

[1]  T. J. Cavicchi,et al.  Numerical study of higher-order diffraction tomography via the sinc basis moment method. , 1989, Ultrasonic imaging.

[2]  M. J. Berggren,et al.  Nonperturbative Diffraction Tomography via Gauss-Newton Iteration Applied to the Scattering Integral Equation , 1992 .

[3]  Michael Brady,et al.  A Representation for Mammographic Image Processing , 1995, CVRMed.

[4]  Aaas News,et al.  Book Reviews , 1893, Buffalo Medical and Surgical Journal.

[5]  P N Wells,et al.  Ultrasonics in clinical diagnosis. , 1966, The Scientific basis of medicine annual reviews.

[6]  Michael Brady,et al.  A Representation for Mammographic Image Processing , 1995, CVRMed.

[7]  P L Carson,et al.  Anthropomorphic breast phantoms for assessing ultrasonic imaging system performance and for training ultrasonographers: Part I , 1982, Journal of clinical ultrasound : JCU.

[8]  S. Broschat,et al.  Inverse imaging of the breast with a material classification technique. , 1998, The Journal of the Acoustical Society of America.

[9]  E. Madsen,et al.  Ultrasonic shear wave properties of soft tissues and tissuelike materials. , 1983, The Journal of the Acoustical Society of America.

[10]  P L Carson,et al.  Anthropomorphic breast phantoms for assessing ultrasonic imaging system performance and for training ultrasonographers: Part II , 1982, Journal of clinical ultrasound : JCU.

[11]  Y. M. Wang,et al.  Reconstruction of Two-Dimensional Refractive Index Distribution Using the Born Iterative and Distorted Born Iterative Method , 1991 .

[12]  D. Borup,et al.  Accelerated Inverse Scattering Algorithms for Higher Contrast Objects , 1987, IEEE 1987 Ultrasonics Symposium.

[13]  Shira L. Broschat,et al.  The FDTD method for ultrasound pulse propagation through a two‐dimensional model of the human breast , 1993 .

[14]  S L Broschat,et al.  FDTD simulations for ultrasound propagation in a 2-D breast model. , 1996, Ultrasonic imaging.

[15]  Roger F. Harrington,et al.  Field computation by moment methods , 1968 .