A 3-D super resolution (SR) pipeline based on data from a Row-Column (RC) array is presented. The 3 MHz RC array contains 62 rows and 62 columns with a half wavelength pitch. A Synthetic Aperture (SA) pulse inversion sequence with 32 positive and 32 negative row emissions are used for acquiring volumetric data using the SARUS research ultrasound scanner. Data received on the 62 columns are beamformed on a GPU for a maximum volume rate of 156 Hz, when the pulse repetition frequency is 10 kHz. Simulated and 3-D printed point and flow micro-phantoms are used for investigating the approach. The flow micro-phantom contains a 100 µm radius tube injected with the contrast agent SonoVue. The 3-D processing pipeline uses the volumetric envelope data to find the bubble's positions from their interpolated maximum signal and yields a high resolution in all three coordinates. For the point micro-phantom the standard deviation on the position is (20.7, 19.8 , 9.1) µm (x, y, z). The precision estimated for the flow phantom is below 23 µm in all three coordinates, making it possible to locate structures on the order of a capillary in all three dimensions. The RC imaging sequence's point spread function has a size of 0.58 × 1.05 × 0.31 mm 3 (1.17λ ×2.12λ ×0.63λ), so the possible volume resolution is 28,900 times smaller than for SA RC B-mode imaging.

Row-column (RC) arrays have the potential to yield full three-dimensional ultrasound imaging with a greatly reduced number of elements compared to fully populated arrays. They, however, have several challenges due to their special geometry. This review paper summarizes the current literature for RC imaging and demonstrate that full anatomic and functional imaging can attain a high quality using synthetic aperture (SA) sequences and modified delay-and-sum beamforming. Resolution can approach the diffraction limit with an isotropic resolution of half a wavelength with low side-lobe levels, and the field-ofview can be expanded by using convex or lensed RC probes. GPU beamforming allows for 3 orthogonal planes to be beamformed at 30 Hz, providing near real time imaging ideal for positioning the probe and improving the operator's workflow. Functional imaging is also attainable using transverse oscillation and dedicated SA sequence for tensor velocity imaging for revealing the full 3-D velocity vector as a function of spatial position and time for both blood velocity and tissue motion estimation. Using RC arrays with commercial contrast agents can reveal super resolution imaging with isotropic resolution below 20 µm. RC arrays can, thus, yield full 3-D imaging at high resolution, contrast, and volumetric rates for both anatomic and functional imaging with the same number of receive channels as current commercial 1-D arrays.

Ultrasound imaging of flow has seen a tremendous development over the last sixty years from 1-D spectral displays to color flow mapping and the latest Vector Flow Imaging (VFI). The paper gives an overview of the development from current commercial vector flow systems to the latest advances in fast 4-D volumetric visualizations. It includes a description of the radical break with the current sequential data acquisition by the introduction of synthetic aperture imaging, where the whole region of interest is insonified using either spherical or plane waves also known as ultrafast imaging. This makes it possible to track flow continuously in all directions at frame rates of thousands of images per second. The latest research translates this to full volumetric imaging by employing matrix arrays and row-column arrays for full 3-D vector velocity estimation at all spatial points visualized at very high volume rates (4-D).

No abstract

Tracking plays an important role in super-resolution (SR) ultrasound imaging, as it improves the quality and sharpness of the final SR images. Moreover, tracking enables quantification of clinically important parameters, such as blood flow velocity. However, the tracking performance degrades in the presence of complex particle patterns and localization uncertainty due to noise and motion. This work presents and discusses multiple approaches for tracking evaluation and compares a nearestneighbor (NN) with a Kalman tracker through simulations and an in vivo experiment. It is shown that in the presence of a localization uncertainty with a standard deviation (SD) of λ /5, the bias and SD of the velocity estimates reach-1.04 ± 0.9 mm/s and-0.12 ± 0.72 mm/s in the NN and Kalman tracker, respectively (relative to the peak velocity of 10 mm/s). The precision of individual track positions is estimated for an in vivo experiment as 37.95 ± 21.37 µm and 23.9 ± 11.82 µm for the NN and Kalman trackers, respectively. The results indicate that the Kalman tracker achieves a better velocity estimation and reduces localization uncertainty.