Machine-to-Machine Transfer Function in Deep Learning-Based Quantitative Ultrasound

A Transfer Function approach was recently demonstrated to mitigate data mismatches at the acquisition level for a single ultrasound scanner in deep learning (DL) based quantitative ultrasound (QUS). As a natural progression, we further investigate the transfer function approach and introduce a Machine-to-Machine (M2M) Transfer Function, which possesses the ability to mitigate data mismatches at a machine level, i.e., mismatches between two scanners over the same frequency band. This ability opens the door to unprecedented opportunities for reducing DL model development costs, enabling the combination of data from multiple sources or scanners, or facilitating the transfer of DL models between machines with ease. We tested the proposed method utilizing a SonixOne machine and a Verasonics machine. In the experiments, we used a L9-4 array and conducted two types of acquisitions to obtain calibration data: stable and free-hand, using two different calibration phantoms. Without the proposed calibration method, the mean classification accuracy when applying a model on data acquired from one system to data acquired from another system was approximately 50%, and the mean AUC was about 0.40. With the proposed method, mean accuracy increased to approximately 90%, and the AUC rose to the 0.99. Additional observations include that shifts in statistics for the z-score normalization had a significant impact on performance. Furthermore, the choice of the calibration phantom played an important role in the proposed method. Additionally, robust implementation inspired by Wiener filtering provided an effective method for transferring the domain from one machine to another machine, and it can succeed using just a single calibration view without the need for multiple independent calibration frames.Comment: 8 pages, 3 Figure

Scattering by single physically large and weak scatterers in the beam of a single-element transducer

Quantitative ultrasound techniques are generally applied to characterize media whose scattering sites are considered to be small compared to a wavelength. In this study, the backscattered response of single weakly scattering spheres and cylinders with diameters comparable to the beam width of a 2.25 MHz single-element transducer were simulated and measured in the transducer focal plane to investigate the impact of physically large scatterers. The responses from large single spherical scatterers at the focus were found to closely match the plane-wave response. The responses from large cylindrical scatterers at the focus were found to differ from the plane-wave response by a factor of f(−1). Normalized spectra from simulations and measurements were in close agreement: the fall-off of the responses as a function of lateral position agreed to within 2 dB for spherical scatterers and to within 3.5 dB for cylindrical scatterers. In both measurement and simulation, single scatterer diameter estimates were biased by less than 3% for a more highly focused transducer compared to estimates for a more weakly focused transducer. The results suggest that quantitative ultrasound techniques may produce physically meaningful size estimates for media whose response is dominated by scatterers comparable in size to the transducer beam

Improved estimation of parameters of the homodyned K distribution

Abstract-The amplitude distribution of the envelope of backscattered ultrasound depends on tissue microstructure. By fitting measured envelope data to a model, parameters can be estimated to describe properties of underlying tissue. The homodyned K distribution is a general model that encompasses the scattering situations modeled by the Rice, Rayleigh, and K distributions. However, parameter estimation for the homodyned K distribution is not straightforward because the model is analytically complex. Furthermore, effects of frequency-dependent attenuation on parameter estimates need to be assessed. An improved parameter estimation algorithm was developed to quickly and accurately estimate parameters of the homodyned K distribution, i.e., the μ (effective number of scatterers per resolution cell) and k (ratio of coherent to diffuse energy) parameters. Parameter estimates were found by fitting estimates of SNR, skewness, and kurtosis of fractional-order moments of the envelope with theoretical values predicted by the homodyned K distribution. The effects of frequency dependent attenuation were approximated by assuming a Gaussian pulse to determine the shift in center frequency of the pulse and hence change in volume of the resolution cell. Computational phantoms were created with varying attenuation coefficients and scanned using a simulated f/4 transducer with a center frequency of 10 MHz. An average of two scatterers per resolution cell (based on the phantoms with no attenuation) was used. The new estimation algorithm was tested and compared with an existing algorithm (based on the even moments of the homodyned K distribution). The new estimation algorithm was found to produce estimates with lower bias and variance. For example, for μ = 2 and k ranging from 0 to 2 in steps of 0.1, the average variance in the μ parameter estimates was 0.067 for the new algorithm and 0.42 for existing algorithm. For the k parameter estimates, the average variance was 0.0069 for the new algorithm and 0.048 for the old algorithm. In the simulations with no attenuation, the μ parameter estimate was 2.53±0.18. In the phantoms with a linear attenuation coefficient of 0.5 dB·MHz -1 ·cm -1 , the estimate was 4.64±0.54. This compared well with the predicted μ value of 4.98

An Ultrasonic Imaging Speckle Supression and Contrast Enhancement Technique by Means of Frequency Compounding and Coded Excitation

Abstract-A method for improving the contrast resolution of B-mode images is proposed by combining the speckle reduction technique of frequency compounding (FC), and the coded excitation and pulse compression technique called resolution enhancement compression (REC). FC suppresses speckle but at the expense of a reduction in axial resolution. Using REC the axial resolution and bandwidth of the imaging system was doubled. Therefore, by combining REC with FC (REC-FC), the trade-off between axial resolution and contrast enhancement was extended significantly. Simulations and experimental measurements were conducted with a singleelement transducer (f/2.66) having a center frequency of 2.25 MHz and a -3-dB bandwidth of 50%. Simulations and measurements of hyperechoic (+6dB) tissue-mimicking targets were imaged. Two FC cases were evaluated: full-, and half-width of the true impulse response bandwidth. The image quality metrics used to compare REC-FC to conventional pulsing (CP) and CP-FC were: contrast-tonoise ratio (CNR), speckle signal-to-noise ratio and histogram percent overlap. Increases in CNR of 121%, and 230% were obtained in experiments when comparing REC-FC for the full-, and half-width cases to CP. Improved lesion detectability was observed by using REC-FC

High-level synthesis design of scalable ultrafast ultrasound beamformer with single FPGA

Ultrafast ultrasound imaging is essential for advanced ultrasound imaging techniques such as ultrasound localization microscopy (ULM) and functional ultrasound (fUS). Current ultrafast ultrasound imaging is challenged by the ultrahigh data bandwidth associated with the radio frequency (RF) signal, and by the latency of the computationally expensive beamforming process. As such, continuous ultrafast data acquisition and beamforming remain elusive with existing software beamformers based on CPUs or GPUs. To address these challenges, the proposed work introduces a novel method of implementing an ultrafast ultrasound beamformer specifically for ultrafast plane wave imaging (PWI) on a field programmable gate array (FPGA) by using high-level synthesis. A parallelized implementation of the beamformer on a single FPGA was proposed by 1) utilizing a delay compression technique to reduce the delay profile size, which enables both run-time pre-calculated delay profile loading from external memory and delay reuse 2) vectorizing channel data fetching which is enabled by delay reuse, and 3) using fixed summing networks to reduce consumption of logic resources. Our proposed method presents two unique advantages over current FPGA beamformers: 1) high scalability that allows fast adaptation to different FPGA resources and beamforming speed demands by using Xilinx High-Level Synthesis as the development tool, and 2) allow a compact form factor design by using a single FPGA to complete the beamforming instead of multiple FPGAs. With the proposed method, a sustainable average beamforming rate of 4.83 G samples/second in terms of input raw RF sample was achieved. The resulting image quality of the proposed beamformer was compared with the software beamformer on the Verasonics Vantage system for both phantom imaging and in vivo imaging of a mouse brain