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

Improving image contrast using coded excitation for ultrasonic imaging

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A Study on the Reconstruction of Moderate Contrast Targets Using the Distorted Born Iterative Method

Abstract-Previous tomographic methods using ultrasound for reconstructing sound speed and attenuation images suffered from convergence issues for targets with moderate speed of sound contrast. Convergence problems can be overcome by the use of the multiple frequency, distorted Born iterative method (DBIM). The implementation of DBIM for measurement configurations in which receiver positions are fixed was studied, and a novel regularization scheme was developed. The regularization parameter needed to stabilize the inversion process initially was found through the Rayleigh quotient iteration, then relaxed according to the relative residual error between the measured and estimated scattered fields. The DBIM was successfully stabilized for both full and partial receiver angular coverage without a significant loss in spatial resolution. The effects of variable density in the reconstructions were briefly explored through simulations. The ability to reconstruct targets with moderate contrast was validated through experimental measurements. Speed of sound profiles for balloons filled with saline in a background of water were reconstructed using multiple frequency DBIM techniques. The mean squared error for speed of sound reconstructions of the balloon phantoms with 16.4% sound speed contrast was 1.1%

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