Transmit Center Frequency Research Articles

Deep Learning for Ultrasound Localization Microscopy.

By localizing microbubbles (MBs) in the vasculature, ultrasound localization microscopy (ULM) has recently been proposed, which greatly improves the spatial resolution of ultrasound (US) imaging and will be helpful for clinical diagnosis. Nevertheless, several challenges remain in fast ULM imaging. The main problems are that current localization methods used to implement fast ULM imaging, e.g., a previously reported localization method based on sparse recovery (CS-ULM), suffer from long data-processing time and exhaustive parameter tuning (optimization). To address these problems, in this paper, we propose a ULM method based on deep learning, which is achieved by using a modified sub-pixel convolutional neural network (CNN), termed as mSPCN-ULM. Simulations and in vivo experiments are performed to evaluate the performance of mSPCN-ULM. Simulation results show that even if under high-density condition (6.4 MBs/mm2), a high localization precision ( [Formula: see text] in the lateral direction and [Formula: see text] in the axial direction) and a high localization reliability (Jaccard index of 0.66) can be obtained by mSPCN-ULM, compared to CS-ULM. The in vivo experimental results indicate that with plane wave scan at a transmit center frequency of 15.625 MHz, microvessels with diameters of [Formula: see text] can be detected and adjacent microvessels with a distance of [Formula: see text] can be separated. Furthermore, when using GPU acceleration, the data-processing time of mSPCN-ULM can be shortened to ~6 sec/frame in the simulations and ~23 sec/frame in the in vivo experiments, which is 3-4 orders of magnitude faster than CS-ULM. Finally, once the network is trained, mSPCN-ULM does not need parameter tuning to implement ULM. As a result, mSPCN-ULM opens the door to implement ULM with fast data-processing speed, high imaging accuracy, short data-acquisition time, and high flexibility (robustness to parameters) characteristics.

Improved Super-Resolution Ultrasound Microvessel Imaging With Spatiotemporal Nonlocal Means Filtering and Bipartite Graph-Based Microbubble Tracking

Super-resolution ultrasound microvessel imaging with contrast microbubbles has recently been proposed by multiple studies, demonstrating outstanding resolution with high potential for clinical applications. This paper aims at addressing the potential noise issue in in vivo human super-resolution imaging with ultrafast plane-wave imaging. The rich spatiotemporal information provided by ultrafast imaging presents features that allow microbubble signals to be separated from background noise. In addition, the high-frame-rate recording of microbubble data enables the implementation of robust tracking algorithms commonly used in particle tracking velocimetry. In this paper, we applied the nonlocal means (NLM) denoising filter on the spatiotemporal domain of the microbubble data to preserve the microbubble tracks caused by microbubble movement and suppress random background noise. We then implemented a bipartite graph-based pairing method with the use of persistence control to further improve the microbubble signal quality and microbubble tracking fidelity. In an in vivo rabbit kidney perfusion study, the NLM filter showed effective noise rejection and substantially improved microbubble localization. The bipartite graph pairing and persistence control demonstrated further noise reduction, improved microvessel delineation, and a more consistent microvessel blood flow speed measurement. With the proposed methods and freehand scanning on a free-breathing rabbit, a single microvessel cross-sectional profile with full-width at half-maximum of could be imaged at approximately 2-cm depth (ultrasound transmit center frequency = 8 MHz, theoretical spatial resolution ). Cortical microvessels that are apart can also be clearly separated. These results suggest that the proposed methods have good potential in facilitating robust in vivo clinical super-resolution microvessel imaging.

Delay-Encoded Harmonic Imaging (DE-HI) in Multiplane-Wave Compounding.

The development of ultrafast ultrasound imaging brings great opportunities to improve imaging technologies such as shear wave elastography and ultrafast Doppler imaging. In ultrafast imaging, several tilted plane or diverging wave images are coherently combined to form a compounded image, leading to trade-offs among image signal-to-noise ratio (SNR), resolution, and post-compounded frame rate. Multiplane wave (MW) imaging is proposed to solve this trade-off by encoding multiple plane waves with Hadamard matrix during one transmission event (i.e. pulse-echo event), to improve image SNR without sacrificing the resolution or frame rate. However, it suffers from stronger reverberation artifacts in B-mode images compared to standard plane wave compounding due to longer transmitted pulses. If harmonic imaging can be combined with MW imaging, the reverberation artifacts and other clutter noises such as sidelobes and multipath scattering clutters should be suppressed. The challenge, however, is that the Hadamard codes used in MW imaging cannot encode the 2nd harmonic component by inversing the pulse polarity. In this paper, we propose a delay-encoded harmonic imaging (DE-HI) technique to encode the 2nd harmonic with a one quarter period delay calculated at the transmit center frequency, rather than reversing the pulse polarity during multiplane wave emissions. Received DE-HI signals can then be decoded in the frequency domain to recover the signals as in single plane wave emissions, but mainly with improved SNR at the 2nd harmonic component instead of the fundamental component. DE-HI was tested experimentally with a point target, a B-mode imaging phantom, and in-vivo human liver imaging. Improvements in image contrast-to-noise ratio (CNR), spatial resolution, and lesion-signal-to-noise ratio ( l SNR) have been achieved compared to standard plane wave compounding, MW imaging, and standard harmonic imaging (maximal improvement of 116% on CNR and 115% on l SNR as compared to standard HI around 55 mm depth in the B-mode imaging phantom study). The potential high frame rate and the stability of encoding and decoding processes of DE-HI were also demonstrated, which made DE-HI promising for a wide spectrum of imaging applications.

Signal to noise ratio comparisons for ultrasound attenuation slope estimation algorithms

Attenuation imaging has a promising role in the detection of tissue abnormalities. The authors have previously compared three different frequency domain ultrasound attenuation estimation methods, for accuracy and bias. The mean estimated attenuation value in a region of interest has been the determining factor of how well a method performs; however, the noise level has not been quantified for attenuation estimated using different methods. The authors compare three different frequency domain ultrasound attenuation estimation methods [the reference phantom method (RPM), the centroid downshift method (CEN), and the hybrid method (HYB)] using the signal to noise ratio (SNR) metric. Both simulated and experimental tissue-mimicking phantoms are used in the performance comparison study, evaluating the impact of the variation in acoustical properties. For attenuation estimation in a tissue-mimicking phantom with a known attenuation coefficient of 0.5 dB/cm/MHz, all the three methods estimated the attenuation coefficient to be ≈ 0.49 dB/cm/MHz for a transmit center frequency of 6 MHz, however, the signal to noise ratio obtained was found to be 8.5, 5.7, and 2.2 for the HYB, RPM, and CEN methods, respectively. These results demonstrate the need for the SNR metric in the comparison of different algorithms and to evaluate the impact of varying different ultrasound system and tissue parameters. In this paper, the authors demonstrate that although the estimated mean attenuation value with a region of interest may be closely estimated using different methods, the signal to noise ratio obtained of the estimates can vary significantly. The centroid downshift method presented with the lowest signal-to-noise ratio of the methods compared. The hybrid method was the least susceptible to changes in the acoustical properties and provided unbiased attenuation coefficient estimates with the highest signal-to-noise ratios.

Evaluation of the impact of backscatter intensity variations on ultrasound attenuation estimation

Quantitative ultrasound based approaches such as attenuation slope estimation can be used to determine underlying tissue properties and eventually used as a supplemental diagnostic technique to B-mode imaging. The authors investigate the impact of backscatter intensity and frequency dependence variations on the attenuation slope estimation accuracy. The authors compare three frequency domain based attenuation slope estimation algorithms, namely, a spectral difference method, the reference phantom method, and two spectral shift methods: a hybrid method and centroid downshift method. Both the reference phantom and hybrid method use a tissue-mimicking phantom with well-defined acoustic properties to reduce system dependencies and diffraction effects. The normalized power spectral ratio obtained is then filtered by a Gaussian filter centered at the transmit center frequency in the hybrid method. A spectral shift method is then used to estimate the attenuation coefficient from the normalized and filtered spectrum. The centroid downshift method utilizes the shift in power spectrum toward lower frequencies with depth. Numerical phantoms that incorporate variations in the backscatter intensity from -3 to 3 dB, by varying the scatterer number density and variations in the scatterer diameters ranging from 10 to 100 μm are simulated. Experimental tissue mimicking phantoms with three different scatterer diameter ranges (5-40, 75-90, and 125-150 μm) are also used to evaluate the accuracy of the estimation methods. The reference phantom method provided accurate results when the acoustical properties of the reference and the sample are well matched. Underestimation occurs when the reference phantom possessed a higher sound speed than the sample, and overestimation occurs when the reference phantom had a lower sound speed than the sample. The centroid downshift method depends significantly on the bandwidth of the power spectrum, which in turn depends on the frequency dependence of the backscattering. The hybrid method was the least susceptible to changes in the sample's acoustic properties and provided the lowest standard deviation in the numerical simulations and experimental evaluations. No significant variations in the estimation accuracy of the attenuation coefficient were observed with an increase in the scatterer number density in the simulated numerical phantoms for the three methods. Changes in the scatterer diameters, which result in different frequency dependence of backscatter, do not significantly affect attenuation slope estimation with the reference phantom and hybrid approaches. The centroid method is sensitive to variations in the scatterer diameter due to the frequency shift introduced in the power spectrum.

Robust and Accurate Ultrasound 3-D Imaging Algorithm Incorporating Adaptive Smoothing Techniques

Many researchers have proposed ultrasound imaging techniques for product inspection; however, most of these techniques are aimed at detecting the existence of flaws in products. The acquisition of an accurate three-dimensional image using ultrasound has the potential to be a useful product inspection tool. In this paper we apply the Envelope algorithm, which was originally proposed for accurate UWB (Ultra Wide-Band) radar imaging systems, to ultrasound imaging. We show that the Envelope algorithm results in image deterioration, because it is difficult for ultrasound measurements to achieve high signal to noise (S/N) ratio values as a result of a high level of noise and interference from the environment. To reduce errors, we propose two adaptive smoothing techniques that effectively stabilize the estimated image produced by the Envelope algorithm. An experimental study verifies that the proposed imaging algorithm has accurate 3-D imaging capability with a mean error of 6.1µm, where the transmit center frequency is 2.0MHz and the S/N ratio is 23dB. These results demonstrate the robustness of the proposed imaging algorithm compared with a conventional Envelope algorithm.

Hybrid Spectral Domain Method for Attenuation Slope Estimation

Attenuation estimation methods for medical ultrasound are important because attenuation properties of soft tissue can be used to distinguish between benign and malignant tumors and to detect diffuse disease. The classical spectral shift method and the spectral difference method are the most commonly used methods for the estimation of the attenuation; however, they both have specific limitations. Classical spectral shift approaches for estimating ultrasonic attenuation are more sensitive to local spectral noise artifacts and have difficulty in compensating for diffraction effects because of beam focusing. Spectral difference approaches, on the other hand, fail to accurately estimate attenuation coefficient values at tissue boundaries that also possess variations in the backscatter. In this paper, we propose a hybrid attenuation estimation method that combines the advantages of the spectral difference and spectral shift methods to overcome their specific limitations. The proposed hybrid method initially uses the spectral difference approach to reduce the impact of system-dependent parameters including diffraction effects. The normalized power spectrum that includes variations because of backscatter changes is then filtered using a Gaussian filter centered at the transmit center frequency of the system. A spectral shift method, namely the spectral cross-correlation algorithm is then used to compute spectral shifts from these filtered power spectra to estimate the attenuation coefficient. Ultrasound simulation results demonstrate that the estimation accuracy of the hybrid method is better than the centroid downshift method (spectral shift method), in uniformly attenuating regions. In addition, this method is also stable at boundaries with variations in the backscatter when compared with the reference phantom method (spectral difference method). Experimental results using tissue-mimicking phantom also illustrate that the hybrid method is more robust and provides accurate attenuation estimates in both uniformly attenuating regions and across boundaries with backscatter variations. The proposed hybrid method preserves the advantages of both the spectral shift and spectral difference approaches while eliminating the disadvantages associated with each of these methods, thereby improving the accuracy and robustness of the attenuation estimation. (E-mail: hyungsukkim@wisc.edu)

Enhancement of Vascular Permeability with Low-Frequency Contrast-enhanced Ultrasound in the Chorioallantoic Membrane Model

To characterize the effect of low-frequency contrast material-enhanced ultrasound on the vascular endothelium and to determine the parameters and techniques required to deliver a therapeutic agent by using the chorioallantoic membrane (CAM) model. All in vivo animal procedures were conducted with institutional Animal Care and Use Committee approval. Extravasation of 8.5-nm-diameter fluorescein isothiocyanate-labeled dextran was evaluated in the vasculature of a chick CAM model. Intravital microscopy was performed during contrast-enhanced ultrasound exposure (1.00 or 2.25 MHz); results were compared with results of electron microscopy of the insonated regions. Data acquired after insonation with greater mechanical stress (n = 30 animals) (mechanical index [MI] > 1.3) and with lower mechanical stress (n = 86 animals) (MI < 1.13) were compared with measurements in control conditions (n = 46 animals). The diameter of affected vessels; number of extravasation sites; extravasation rate, area, and location; and changes in endothelial cells and basement membrane were evaluated. Differences were tested with analysis of variance or the Student t test. After ultrasound application, convective transport of the model drug was observed through micron-sized openings with a mean fluid velocity of 188.6 microm/sec in the low-stress class and 362.5 microm/sec in the high-stress class. Electron microscopy revealed micron-sized focal endothelial gaps and disseminated blebs, vacuoles, and filopodia extending across tens of microns. The threshold pressure for extravasation was 0.5 MPa for a transmitted center frequency of 1.00 MHz (MI = 0.5) and 1.6 MPa for a frequency of 2.25 MHz (MI = 1.06); thus, the frequency dependence of the threshold was not predicted simply by the MI. Low-frequency contrast-enhanced ultrasound can increase vascular permeability and result in convective extravasation of an 8.5-nm-diameter model drug.