Proper spatial sampling is critical for high quality imaging. If the sampling criterion is not met, grating lobe artifacts appear in the image. In non-destructive testing applications efficiency is being increased by the steady enlargement of the field of view, resulting in more elements and thus a higher transducer complexity and cost. In the volume scanning methods used in medical applications, the challenge lies in connecting the 2500+ elements of a matrix array to <256 channels. Usually pre-beamforming is used to reduce the data at the cost of image quality. An alternative is to reconstruct the non-aliased data from spatially aliased data. Last year we reported a reconstruction method based on wave field extrapolation, which performs best for a limited depth range. In this work the method is extended to cover the entire imaging range at once. Its performance is investigated using phased array data of a tissue phantom. To reconstruct the traces the technique uses an iterative scheme based on a fast wavenumber-frequency domain mapping (Stolt migration) and its inverse in combination with thresholding to exclude the aliasing artifacts in the imaging domain. A properly sampled dataset was recorded of a tissue mimicking phantom using a linear phased array transducer connected to a research scanner for full channel data capture. From this dataset, undersampled datasets were created by selecting a limited number of channels. The datasets were imaged using wavenumber-frequency domain mapping (Stolt migration). The reconstruction method significantly improved the image quality of the aliased datasets.

, , ,
doi.org/10.1109/ULTSYM.2016.7728460, hdl.handle.net/1765/94426
2016 IEEE International Ultrasonics Symposium, IUS 2016
Department of Biomedical Engineering

van Neer, P., Vos, R., & Volker, A.F.W. (2016). Stolt migration based iterative trace reconstruction. In IEEE International Ultrasonics Symposium, IUS. doi:10.1109/ULTSYM.2016.7728460