No abstract

No abstract

High-frame-rate volume imaging (HFR-VI) aims to provide high-quality images with high-temporal information. Despite its potential, HFR-VI translation into clinical applications has been challenging due to the high cost of the equipment required to drive matrix probes with a large number of elements. The goal of this study is to introduce and test sparse-random-aperture compounding (SRAC), a technique that allows use of matrix probes with an ultrasound system that has fewer channels while maintaining high frame rates. Four scanning methods were implemented with a 256-channel system using a 4-to-1 multiplexer and a 3 MHz matrix probe with 1024 elements. These methods used three types of waves, either single-diverging waves (SDW), multiplane-diverging waves (MDW) or wide beams (WB); and were driven using one to four SRAC. All methods were also implemented in a 1024-channel multisystem. The main-lobe-to-side-lobe ratio (MLSLR) and the contrast ratio (CR) were studied using a string phantom and a CIRS phantom, respectively. The results showed an increase in the MLSLR and CR as a function of the number of SRAC. The multisystem provided the best results for the MLSLR. However, four SRAC outperformed the multisystem with respect to CR. The method using SDW provided the highest frame rates (i.e. 1875 and 7500 Hz for four and one SRAC, respectively), however it provided the lowest image quality. The two methods using MDWs showed a good compromise between image quality and frame rate (i.e. 187 to 750 Hz for four and one SRAC). WB provided the best image quality at the expense of frame rate (i.e. 18 to 75 Hz for four and one SRAC). Our results suggest that SRAC in combination with the tested scanning methods can provide a low-channel count alternative for HFR-VI systems and allows a tunable tradeoff between image quality and frame rate guided by the desired application.

Vector velocity blood flow imaging gives speed and direction of blood flow at each pixel. An imaging algorithm proposed earlier [2] requires multiple angles of planewave (PW) transmissions to construct a robustly invertible model for vector velocity estimates.Here we demonstrate a vector velocity estimation approach that requires only a single planewave transmission angle. The proposed algorithm uses PW transmission and reconstruction to generate a blood motion image sequence in the B-mode flow (B-Flow) modality, at frame rates in the Doppler PRF regime. Pixel ensembles in the image sequence at point p = [x, z] and pulse t are comprised of IQ magnitude values, computed from the IQ data at each pixel p after wall filtering the ensemble. The sequence of values thus captures motion at a framerate equal to the PRF, revealing fine-scale flow dynamics as a moving texture in the blood reflectivity.Using the chain rule, spatial and temporal derivatives resulting from the space-time gradient of the image sequence couple to the texture flow velocity vector field [vx(x, z, t), vz(x, z, t)] at each pixel p and PRI t. The resulting Gauss-Markov models are solved by least squares to give the vector velocity estimates, which are formulated in the model to be constant over the estimation window.We also evaluate variants that include in the observation, lagproduct samples (autocorrelation summands) at non-zero lags, as well as instantaneous Doppler-derived axial velocity estimates.Compared to the multi-angle planewave algorithm presented in [2], this approach allows for a longer time interval for wall filtering, as the frame is not partitioned into separate segments for different planewave angles. This permits wall filters with steeper transition bands, and allows flexibility in balancing framerate and sensitivity, suggesting application to vector flow imaging of deep tissue where efficiently achieving planewave angle diversity at the target becomes difficult.Using a Philips L7-4 transducer and a Verasonics (TM) acquisition system, we evaluate single-angle PWT vector velocity imaging on a Doppler string phantom, and demonstrate it successfully on a carotid artery.

No abstract