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Three-dimensional (3-D) ultrasound imaging of the breast enables better assessment of diseases than conventional two-dimensional (2-D) imaging. Free-hand techniques are often used for generating 3-D data from a sequence of 2-D slice images. However, the breast deforms substantially during scanning because it is composed primarily of soft tissue. This often causes tissue mis-registration in spatial compounding of multiple scan sweeps. To overcome this problem, in this paper, instead of introducing additional constraints on scanning conditions, we use image processing techniques. We present a fully automatic algorithm for 3-D nonlinear registration of free-hand ultrasound data. It uses a block matching scheme and local statistics to estimate local tissue deformation. A Bayesian regularization method is applied to the sample displacement field. The final deformation field is obtained by fitting a B-spline approximating mesh to the sample displacement field. Registration accuracy is evaluated using phantom data and similar registration errors are achieved with (0.19 mm) and without (0.16 mm) gaps in the data. Experimental results show that registration is crucial in spatial compounding of different sweeps. The execution time of the method on moderate hardware is sufficiently fast for fairly large research studies.

Original publication

DOI

10.1109/TMI.2002.1000264

Type

Journal article

Journal

IEEE Trans Med Imaging

Publication Date

04/2002

Volume

21

Pages

405 - 412

Keywords

Algorithms, Anisotropy, Bayes Theorem, Breast Neoplasms, Fibroadenoma, Humans, Image Enhancement, Imaging, Three-Dimensional, Models, Statistical, Nonlinear Dynamics, Phantom Limb, Reproducibility of Results, Sensitivity and Specificity, Ultrasonography, Mammary