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.
Super resolution (SR) imaging is currently conducted using fragile ultrasound contrast agents. This precludes using the full acoustic pressure range, and the distribution of bubbles has to be sparse for them to be isolated for SR imaging. Images have to be acquired over minutes to accumulate enough positions for visualizing the vasculature. A new method for SUper Resolution imaging using the Erythrocytes (SURE) as targets is introduced, which makes it possible to maximize the emitted pressure for good signal-to-noise ratios. The abundant number of erythrocyte targets make acquisition fast, and the SURE images can be acquired in seconds. A Verasonics Vantage 256 scanner was used in combination with a GE L8-18iD linear array probe operated at 10 MHz for a wavelength of 150 µm. A 12 emissions synthetic aperture ultrasound sequence was employed to scan the kidney of a Sprague-Dawley rat for 24 seconds to visualize its vasculature. An ex vivo micro-CT image using the contrast agent Microfil was also acquired at a voxel size of 22.6 µm for validating the SURE images. The SURE image revealed vessels with a size down to 29 µm, five times smaller than the ultrasound wavelength, and the dense grid of vessels in the full kidney was reliably shown for scan times between 1 to 24 seconds. Visually the SURE images revealed the same vasculature as the micro-CT images. SURE images are acquired in seconds rather than minutes without contrast injection for easy clinical use, and they can be measured at full regulatory levels for pressure, intensity, and probe temperature.
A delay-and-sum beamformer implementation for 3D imaging with row-column arrays is presented. It is written entirely in the MATLAB programming language for flexible use and fast modifications for research use, and all parts can run on either the CPU or GPU. Dynamic apodization with row-column arrays is presented and is supported in both transmit and receive. Delay calculations are simplified compared to previous beamformers, and 3D delay and apodization calculations are reduced to 2D problems for faster calculations. The performance is evaluated on an Intel Xeon E5-2630 v4 CPU with 64 GB RAM and a NVIDIA GeForce GTX 1080 Ti GPU with 11 GB RAM. A 192+192 array is simulated to image a volume of 96-by-96-by-45 wavelengths sampled at 0.3 wavelength in the axial direction and 0.5 wavelength in the lateral and elevation directions giving 5.53 million sample points. A single-element synthetic aperture sequence with 192 emissions is used. The 192 volumes are beamformed in approximately 1 hour on the CPU and 5 minutes on the GPU corresponding to a speed-up of up to 12.2 times. For a smaller beamforming problem consisting of the three center planes in the volume, a speed-up of 4.6 times is found from 109 to 24 seconds. The GPU utilization is around 5.0% of the possible floating point calculations indicating a trade-off between the easy programming approach and high performance.
Two delay-and-sum beamformers for 3-D synthetic aperture imaging with row-column addressed arrays are presented. Both beamformers are software implementations for graphics processing unit (GPU) execution with dynamic apodizations and 3rd order polynomial subsample interpolation. The first beamformer was written in the MATLAB programming language and the second was written in C/C++ with the compute unified device architecture (CUDA) extensions by NVIDIA. Performance was measured as volume rate and sample throughput on three different GPUs: a 1050 Ti, a 1080 Ti, and a TITAN V. The beamformers were evaluated across 112 combinations of output geometry, depth range, transducer array size, number of virtual sources, floating point precision, and Nyquist rate or inphase/quadrature beamforming using analytic signals. Real-time imaging defined as more than 30 volumes per second was attained by the CUDA beamformer on the three GPUs for 13, 27, and 43 setups, respectively. The MATLAB beamformer did not attain real-time imaging for any setup. The median, single precision sample throughput of the CUDA beamformer was 4.9, 20.8, and 33.5 gigasamples per second on the three GPUs, respectively. The CUDA beamformer's throughput was an order of magnitude higher than that of the MATLAB beamformer.
The improved resolution provided by ultrasound super-resolution imaging (SRI) sets new demands on the fabrication of phantoms for the validation and verification of the technique. Phantoms should resemble tissue and replicate the 3D nature of tissue vasculature at the microvascular scale. This paper presents a potential method for creating complex 3D phantoms, via 3D printing of water-filled polymer networks. By using a custom-built stereolithographic printer, projected light of the desired patterns converts an aqueous poly(ethylene glycol) diacrylate (PEGDA) solution into a hydrogel, a material capable of containing 75 wt% of water. Due to the hydrogel mainly consisting of water, it will, from an acoustical point of view, respond very similar to tissue. A method for printing cavities as small as (100 µm) 3 is demonstrated, and a 3D printed flow phantom containing channels with cross sections of (200 µm) 2 is presented. The designed structures are geometrically manufactured with a 2% increase in dimensions. The potential for further reduction of the flow phantom channels size, makes 3D printing a promising method for obtaining microvascular-like structures.
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