Adaptive imaging and spatial compounding in the presence of aberration

Mitigating Aberration-Induced Noise: A Deep Learning-Based Aberration-to- Aberration Approach

One of the primary sources of suboptimal image quality in ultrasound imaging is phase aberration. It is caused by spatial changes in sound speed over a heterogeneous medium, which disturbs the transmitted waves and prevents coherent summation of echo signals. Obtaining non-aberrated ground truths in real-world scenarios can be extremely challenging, if not impossible. This challenge hinders the performance of deep learning-based techniques due to the domain shift between simulated and experimental data. Here, for the first time, we propose a deep learning-based method that does not require ground truth to correct the phase aberration problem and, as such, can be directly trained on real data. We train a network wherein both the input and target output are randomly aberrated radio frequency (RF) data. Moreover, we demonstrate that a conventional loss function such as mean square error is inadequate for training such a network to achieve optimal performance. Instead, we propose an adaptive mixed loss function that employs both B-mode and RF data, resulting in more efficient convergence and enhanced performance. Finally, we publicly release our dataset, comprising over 180,000 aberrated single plane-wave images (RF data), wherein phase aberrations are modeled as near-field phase screens. Although not utilized in the proposed method, each aberrated image is paired with its corresponding aberration profile and the non-aberrated version, aiming to mitigate the data scarcity problem in developing deep learning-based techniques for phase aberration correction. Source code and trained model are also available along with the dataset at https://code.sonography.ai/main-aaa.

Aberration correction in diagnostic ultrasound: A review of the prior field and current directions

Medical ultrasound images are reconstructed with simplifying assumptions on wave propagation, with one of the most prominent assumptions being that the imaging medium is composed of a constant sound speed. When the assumption of a constant sound speed are violated, which is true in most in vivoor clinical imaging scenarios, distortion of the transmitted and received ultrasound wavefronts appear and degrade the image quality. This distortion is known as aberration, and the techniques used to correct for the distortion are known as aberration correction techniques. Several models have been proposed to understand and correct for aberration. In this review paper, aberration and aberration correction are explored from the early models and correction techniques, including the near-field phase screen model and its associated correction techniques such as nearest-neighbor cross-correlation, to more recent models and correction techniques that incorporate spatially varying aberration and diffractive effects, such as models and techniques that rely on the estimation of the sound speed distribution in the imaging medium. In addition to historical models, future directions of ultrasound aberration correction are proposed.

Adaptive subarray coherence based post-filter using array gain in medical ultrasound imaging

This paper presents an adaptive subarray coherence-based post-filter (ASCBP) applied to the eigenspace-based forward-backward minimum variance (ESB-FBMV) beamformer to simultaneously improve image quality and beamformer robustness. Additionally, the ASCBP can separate close targets. The ASCBP uses an adaptive noise power weight based on the concept of the beamformer's array gain (AG) to suppress the noise adaptively and achieve improved images. Moreover, a square neighborhood average was applied to the ASCBP in order to provide more smoothed square neighborhood ASCBP (SN-ASCBP) values and improve the speckle quality. Through simulations of point phantoms and cyst phantoms and experimental validation, the performance of the proposed methods was compared to that of delay-and-sum (DAS), MV-based beamformers, and subarray coherence-based post-filter (SCBP). The simulated results demonstrated that the ASCBP method improved the full width at half maximum (FWHM) by 57 % and the coherent interference suppression power (CISP) by 52 dB compared to the SCBP post-filter. Considering the experimental results, the SN-ASCBP method presented the best enhancement in terms of generalized contrast to noise ratio (gCNR) and contrast ratio (CR) while the ASCBP showed the best improvement in FWHM among other methods. Furthermore, the proposed methods presented a striking performance in low SNRs. The results of evaluating the different methods under aberration and sound speed error illustrated the better robustness of the proposed methods in comparison with others.

Effects of phase aberration on transabdominal focusing for a large aperture, lowf-number histotripsy transducer

Objective. Soft tissue phase aberration may be particularly severe for histotripsy due to large aperture and lowf-number transducer geometries. This study investigated how phase aberration from human abdominal tissue affects focusing of a large, strongly curved histotripsy transducer.Approach.A computational model (k-Wave) was experimentally validated withex vivoporcine abdominal tissue and used to simulate focusing a histotripsy transducer (radius: 14.2 cm,f-number: 0.62, central frequencyfc: 750 kHz) through the human abdomen. Abdominal computed tomography images from 10 human subjects were segmented to create three-dimensional acoustic property maps. Simulations were performed focusing at 3 target locations in the liver of each subject with ideal phase correction, without phase correction, and after separately matching the sound speed of water and fat to non-fat soft tissue.Main results.Experimental validation in porcine abdominal tissue showed that simulated and measured arrival time differences agreed well (average error, ∼0.10 acoustic cycles atfc). In simulations with human tissue, aberration created arrival time differences of 0.65μs (∼0.5 cycles) at the target and shifted the focus from the target by 6.8 mm (6.4 mm pre-focally along depth direction), on average. Ideal phase correction increased maximum pressure amplitude by 95%, on average. Matching the sound speed of water and fat to non-fat soft tissue decreased the average pre-focal shift by 3.6 and 0.5 mm and increased pressure amplitude by 2% and 69%, respectively.Significance.Soft tissue phase aberration of large aperture, lowf-number histotripsy transducers is substantial despite low therapeutic frequencies. Phase correction could potentially recover substantial pressure amplitude for transabdominal histotripsy. Additionally, different heterogeneity sources distinctly affect focusing quality. The water path strongly affects the focal shift, while irregular tissue boundaries (e.g. fat) dominate pressure loss.

Adaptive Models for Multi-Covariate Imaging of Sub-Resolution Targets (MIST)

Multi-covariate imaging of sub-resolution targets (MIST) is a statistical, model-based image formation technique that smooths speckles and reduces clutter. MIST decomposes the measured covariance of the element signals into modeled contributions from mainlobe, sidelobes, and noise. MIST covariance models are derived from the well-known autocorrelation relationship between transmit apodization and backscatter covariance. During in vivo imaging, the effective transmit aperture often deviates from the applied apodization due to nonlinear propagation and wavefront aberration. Previously, the backscatter correlation length provided a first-order measure of these patient-specific effects. In this work, we generalize and extend this approach by developing data-adaptive covariance estimation, parameterization, and model-formation techniques. We performed MIST imaging using these adaptive models and evaluated the performance gains using 152 tissue-harmonic scans of fetal targets acquired from 15 healthy pregnant subjects. Compared to standard MIST imaging, the contrast-to-noise ratio (CNR) is improved by a median of 8.3%, and the speckle signal-to-noise ratio (SNR) is improved by a median of 9.7%. The median CNR and SNR gains over B-mode are improved from 29.4% to 40.4% and 24.7% to 38.3%, respectively. We present a versatile empirical function that can parameterize an arbitrary speckle covariance and estimate the effective coherent aperture size and higher order coherence loss. We studied the performance of the proposed methods as a function of input parameters. The implications of system-independent MIST implementation are discussed.

Switchable and Tunable Deep Beamformer Using Adaptive Instance Normalization for Medical Ultrasound

Recent proposals of deep learning-based beamformers for ultrasound imaging (US) have attracted significant attention as computational efficient alternatives to adaptive and compressive beamformers. Moreover, deep beamformers are versatile in that image post-processing algorithms can be readily combined. Unfortunately, with the existing technology, a large number of beamformers need to be trained and stored for different probes, organs, depth ranges, operating frequency, and desired target 'styles', demanding significant resources such as training data, etc. To address this problem, here we propose a switchable and tunable deep beamformer that can switch between various types of outputs such as DAS, MVBF, DMAS, GCF, etc., and also adjust noise removal levels at the inference phase, by using a simple switch or tunable nozzle. This novel mechanism is implemented through Adaptive Instance Normalization (AdaIN) layers, so that distinct outputs can be generated using a single generator by merely changing the AdaIN codes. Experimental results using B-mode focused ultrasound confirm the flexibility and efficacy of the proposed method for various applications.

Blood Flow Imaging in the Neonatal Brain Using Angular Coherence Power Doppler

Using ultrasound to image small vessels in the neonatal brain can be difficult in the presence of strong clutter from the surrounding tissue and with a neonate motion during the scan. We propose a coherence-based beamforming method, namely the short-lag angular coherence (SLAC) beamforming that suppresses incoherent noise and motion artifacts in Ultrafast data, and we demonstrate its applicability to improve detection of blood flow in the neonatal brain. Instead of estimating spatial coherence across the receive elements, SLAC utilizes the principle of acoustic reciprocity to estimate angular coherence from the beamsummed signals from different plane-wave transmits, which makes it computationally efficient and amenable to advanced beamforming techniques, such as f-k migration. The SLAC images of a simulated speckle phantom show similar edge resolution and texture size as the matching B-mode images, and reduced random noise in the background. We apply SLAC power Doppler (PD) to free-hand imaging of neonatal brain vasculature with long Doppler ensembles and show that: 1) it improves visualization of small vessels in the cortex compared to conventional PD and 2) it can be used for tracking of blood flow in the brain over time, meaning it could potentially improve the quality of free-hand functional ultrasound.

Assessing the Robustness of Frequency-Domain Ultrasound Beamforming Using Deep Neural Networks

We study training deep neural network (DNN) frequency-domain beamformers using simulated and phantom anechoic cysts and compare to training with simulated point target responses. Using simulation, physical phantom, and in vivo scans, we find that training DNN beamformers using anechoic cysts provided comparable or improved image quality compared with training DNN beamformers using simulated point targets. The proposed method could also be adapted to generate training data from in vivo scans. Finally, we evaluated the robustness of DNN beamforming to common sources of image degradation, including gross sound speed errors, phase aberration, and reverberation. We found that DNN beamformers maintained their ability to improve image quality even in the presence of the studied sources of image degradation. Overall, the results show the potential of using DNN beamforming to improve ultrasound image quality.

Effects of motion on correlations of pulse-echo ultrasound signals: Applications in delay estimation and aperture coherence

The correlation between two pulse-echo ultrasound signals is used to achieve a wide range of ultrasound techniques, such as Doppler imaging and elastography. Prior theoretical descriptions of pulse-echo correlations were restricted to stationary scatterers. Here, a theory for the correlation of moving scatterers is presented. An expression is derived for the correlation of two pulse-echo signals with arbitrary transmit and receive apertures acquired from a medium undergoing bulk motion using the Fresnel approximation. The derivation is shown to coincide with prior derivations in the absence of scatterer motion. The theory was compared against simulations in applications of phase-shift estimation and aperture coherence measurements. The phase-shift estimate and jitter were accurately predicted under axial and transverse motion for focused transmit apertures and for sequential and interleaved synthetic transmit apertures. The theory also accurately predicted how motion affects the correlation coefficient between receive aperture elements for a synthetic transmit aperture. The presented theory provides a framework for analyzing the correlations of arbitrary pulse-echo configurations for applications in which scatterer motion is expected.

Beamforming and Speckle Reduction Using Neural Networks

With traditional beamforming methods, ultrasound B-mode images contain speckle noise caused by the random interference of subresolution scatterers. In this paper, we present a framework for using neural networks to beamform ultrasound channel signals into speckle-reduced B-mode images. We introduce log-domain normalization-independent loss functions that are appropriate for ultrasound imaging. A fully convolutional neural network was trained with the simulated channel signals that were coregistered spatially to ground-truth maps of echogenicity. Networks were designed to accept 16 beamformed subaperture radio frequency (RF) signals. Training performance was compared as a function of training objective, network depth, and network width. The networks were then evaluated on the simulation, phantom, and in vivo data and compared against the existing speckle reduction techniques. The most effective configuration was found to be the deepest (16 layer) and widest (32 filter) networks, trained to minimize a normalization-independent mixture of the l1 and multiscale structural similarity (MS-SSIM) losses. The neural network significantly outperformed delay-and-sum (DAS) and receive-only spatial compounding in speckle reduction while preserving resolution and exhibited improved detail preservation over a nonlocal means method. This work demonstrates that ultrasound B-mode image reconstruction using machine-learned neural networks is feasible and establishes that networks trained solely in silico can be generalized to real-world imaging in vivo to produce images with significantly reduced speckle.

Spatial Prediction Filtering for Medical Ultrasound in Aberration and Random Noise

While medical ultrasound imaging has become one of the most widely used imaging modalities in clinics, it often suffers from suboptimal image quality, especially in technically difficult patients with a large amount of fat content that induces severe phase aberration effects and decreases the signal-to-noise ratio. Several researchers have proposed various techniques, which can be broadly categorized as either a phase aberration correction (PAC) technique or a coherence-based imaging technique, to address the challenges in imaging technically difficult patients. Although both families of techniques have shown some success in improving the image quality in the presence of a mild level of phase aberration and/or random noise, they often fail to achieve meaningful improvements in the image quality and, in some cases, even create severe image artifacts. In this paper, we employ an adaptive filtering technique called frequency-space prediction filtering (FXPF), which we recently introduced in ultrasound imaging, to overcome the weaknesses of existing techniques and achieve image quality improvements more effectively under varying levels of phase aberration and random noise. Using simulated and experimental phantom data with varying levels of phase aberration and random noise, we evaluate and compare the performance of FXPF with the most representative technique for each category: nearest-neighbor cross correlation (NNCC)-based PAC and the generalized coherence factor (GCF). Our simulation, experimental phantom, and in vivo results demonstrate that FXPF is highly robust in varying levels of phase aberration and noise, and always outperforms both NNCC-based PAC and GCF in terms of the contrast-to-noise ratio (CNR) and the contrast when both random noise and phase aberration are present.

Local speed of sound estimation in tissue using pulse-echo ultrasound: Model-based approach

A model and method to accurately estimate the local speed of sound in tissue from pulse-echo ultrasound data is presented. The model relates the local speeds of sound along a wave propagation path to the average speed of sound over the path, and allows one to avoid bias in the sound-speed estimates that can result from overlying layers of subcutaneous fat and muscle tissue. Herein, the average speed of sound using the approach by Anderson and Trahey is measured, and then the authors solve the proposed model for the local sound-speed via gradient descent. The sound-speed estimator was tested in a series of simulation and ex vivo phantom experiments using two-layer media as a simple model of abdominal tissue. The bias of the local sound-speed estimates from the bottom layers is less than 6.2 m/s, while the bias of the matched Anderson's estimates is as high as 66 m/s. The local speed-of-sound estimates have higher standard deviation than the Anderson's estimates. When the mean local estimate is computed over a 5-by-5 mm region of interest, its standard deviation is reduced to less than 7 m/s.

The Impact of Model-Based Clutter Suppression on Cluttered, Aberrated Wavefronts

Recent studies reveal that both phase aberration and reverberation play a major role in degrading ultrasound image quality. We previously developed an algorithm for suppressing clutter, but we have not yet tested it in the context of aberrated wavefronts. In this paper, we evaluate our previously reported algorithm, called aperture domain model image reconstruction (ADMIRE), in the presence of phase aberration and in the presence of multipath scattering and phase aberration. We use simulations to investigate phase aberration corruption and correction in the presence of reverberation. As part of this paper, we observed that ADMIRE leads to suppressed levels of aberration. In order to accurately characterize aberrated signals of interest, we introduced an adaptive component to ADMIRE to account for aberration, referred to as adaptive ADMIRE. We then use ADMIRE, adaptive ADMIRE, and conventional filtering methods to characterize aberration profiles on in vivo liver data. These in vivo results suggest that adaptive ADMIRE could be used to better characterize a wider range of aberrated wavefronts. The aberration profiles' full-width at half-maximum of ADMIRE, adaptive ADMIRE, and postfiltered data with 0.4- mm-1 spatial cutoff frequency are 4.0 ± 0.28 mm, 2.8 ± 1.3 mm, and 2.8 ± 0.57 mm, respectively, while the average root-mean square values in the same order are 16 ± 5.4 ns, 20 ± 6.3 ns, and 19 ± 3.9 ns, respectively. Finally, because ADMIRE suppresses aberration, we perform a limited evaluation of image quality using simulations and in vivo data to determine how ADMIRE and adaptive ADMIRE perform with and without aberration correction.

Coded excitation waveform engineering for high frame rate synthetic aperture ultrasound imaging

Coded excitation was initially introduced to ultrasound imaging as a method for enhancing the signal-to-noise ratio (SNR). However, this method was also shown to be helpful in conjunction with synthetic aperture transmission for high frame rate imaging. Recently, we introduced two families of mismatched coded excitations based on frequency modulation chirp and combined frequency modulation and Golay code. Here "mismatched" indicates that the coded excitations generate very small cross-correlations among themselves while each has a very strong autocorrelation. Employing weakly correlated coded excitations enables performing simultaneous insonifications from several elements of the ultrasonic transducer and receiving distinguishable responses to each code. In this work, we propose and experimentally demonstrate another set of mismatched correlated coded excitations based on Golay codes. The generated phase codes share identical duration and center frequency which results in similar SNR and image resolution.

Combined phase screen aberration correction and minimum variance beamforming in medical ultrasound

In recent years, applying adaptive beamforming to ultrasound imaging improves image quality in terms of resolution and contrast. One of the best adaptive beamformers in this field is the minimum variance (MV) beamformer which presents better resolution and edge definition compared to the traditional delay-and-sum (DAS) beamformer. However, in real situations, sound-velocity inhomogeneities cause phase aberration which leads to ambiguity in targets' location and degradation in resolution. This effect is a fundamental obstacle to utilize advantages of MV beamformer, although, in aberrating medium MV beamformer results in better performance compared to DAS. In this paper, two different levels of phase screens have been applied to simulate aberrator layers located close to the transducer. Also, prior to beamforming process, a conventional correction technique based on phase screen model is used. Simulations are performed in majority resolution of MV which has the lowest robustness. The results demonstrate that applying this correction method can retrieve the efficiency of the MV beamformer. Moreover, the method improves the performance of the MV in both terms of resolution and contrast. As corrected MV achieved at least 22% improvement in sidelobe reduction and 24% increase in contrast to noise ratio (CNR) with respect to the DAS corrected data. Also, according to experimental dataset 17% enhancement in CNR is yielded by MV.

Handheld real-time volumetric imaging of the spine: technology development

Technical difficulties, poor image quality and reliance on pattern identifications represent some of the drawbacks of two-dimensional ultrasound imaging of spinal bone anatomy. To overcome these limitations, this study sought to develop real-time volumetric imaging of the spine using a portable handheld device. The device measured 19.2 cm × 9.2 cm × 9.0 cm and imaged at 5 MHz centre frequency. 2D imaging under conventional ultrasound and volumetric (3D) imaging in real time was achieved and verified by inspection using a custom spine phantom. Further device performance was assessed and revealed a 75-min battery life and an average frame rate of 17.7 Hz in volumetric imaging mode. The results suggest that real-time volumetric imaging of the spine is a feasible technique for more intuitive visualization of the spine. These results may have important ramifications for a large array of neuraxial procedures.

Short-lag spatial coherence imaging on matrix arrays, part 1: Beamforming methods and simulation studies

Short-lag spatial coherence (SLSC) imaging is a beamforming technique that has demonstrated improved imaging performance compared with conventional B-mode imaging in previous studies. Thus far, the use of 1-D arrays has limited coherence measurements and SLSC imaging to a single dimension. Here, the SLSC algorithm is extended for use on 2-D matrix array transducers and applied in a simulation study examining imaging performance as a function of subaperture configuration and of incoherent channel noise. SLSC images generated with a 2-D array yielded superior contrast-to-noise ratio (CNR) and texture SNR measurements over SLSC images made on a corresponding 1-D array and over B-mode imaging. SLSC images generated with square subapertures were found to be superior to SLSC images generated with subapertures of equal surface area that spanned the whole array in one dimension. Subaperture beamforming was found to have little effect on SLSC imaging performance for subapertures up to 8 x 8 elements in size on a 64 × 64 element transducer. Additionally, the use of 8 x 8, 4 x 4, and 2 x 2 element subapertures provided 8, 4, and 2 times improvement in channel SNR along with 2640-, 328-, and 25-fold reduction in computation time, respectively. These results indicate that volumetric SLSC imaging is readily applicable to existing 2-D arrays that employ subaperture beamforming.

Applying Thomson's multitaper approach to reduce speckle in medical ultrasound imaging

To reduce the variance of speckle in coherent imaging systems, one must average images with different speckle realizations. Traditionally, these images have been formed by observing the target region from slightly different angles (spatial compounding) or by varying the involved temporal frequencies (frequency compounding). In this paper, we investigate a third option based on Thomson's multitaper approach to power spectrum estimation. The tapers are applied spatially, as array weights. Our investigations, based on both recorded ultrasound data and simulations, verify that the multitaper approach can be used for speckle reduction at a rate comparable to that of the more traditional method of spatial compounding. Because of the spectral concentration of the tapers, an added benefit is reduced side lobe levels, which can result in steeper edges and better definition of cyst-like structures.

Synergistic enhancements of ultrasound image contrast with a combination of phase aberration correction and dual apodization with cross-correlation

Dual apodization with cross-correlation (DAX) is a novel adaptive beamforming technique which utilizes two distinct apodization functions in suppressing side lobes and clutter. Previous studies have shown that the performance of DAX in minimizing the effects of phase aberration diminishes with increasing aberrator strength. To achieve greater improvement in image contrast, we propose, in this paper, to combine DAX with a phase aberration correction algorithm based on nearest-neighbor cross-correlation (NNCC). Our simulation and experimental results presented in this work showed that the proposed method allows for synergistic enhancements of image contrast and achieves greater improvement in image quality than using DAX alone or phase aberration correction alone in the presence of weak and strong aberrators. Compared with standard delay-and-sum (DAS) beamforming, using the proposed method on simulated data with weak and strong aberrations increased the contrast-to-noise ratio (CNR) values from 4.10 to 10.96 and from 1.69 to 9.80, respectively. Experimental results were obtained using pork tissues of 4 and 10 mm thickness and a tissue-mimicking phantom. The CNR values increased from 3.74 to 9.72 for the 4-mm pork aberrator and from 1.27 to 8.17 for the 10-mm pork aberrator.

Short-lag spatial coherence of backscattered echoes: imaging characteristics

Conventional ultrasound images are formed by delay-and-sum beamforming of the backscattered echoes received by individual elements of the transducer aperture. Although the delay-and-sum beamformer is well suited for ultrasound image formation, it is corrupted by speckle noise and challenged by acoustic clutter and phase aberration. We propose an alternative method of imaging utilizing the short-lag spatial coherence (SLSC) of the backscattered echoes. Compared with matched B-mode images, SLSC images demonstrate superior SNR and contrast-to-noise ratio in simulated and experimental speckle-generating phantom targets, but are shown to be challenged by limited point target conspicuity. Matched B-mode and SLSC images of a human thyroid are presented. The challenges and opportunities of real-time implementation of SLSC imaging are discussed.

A wavelet thresholding method to reduce ultrasound artifacts

Artifacts due to enhancement, reverberation, and multi-path reflection are commonly encountered in medical ultrasound imaging. These artifacts can adversely affect an automated image quantification algorithm or interfere with a physician's assessment of a radiological image. This paper proposes a soft wavelet thresholding method to replace regions adversely affected by these artifacts with the texture due to the underlying tissue(s), which were originally obscured. Our proposed method soft thresholds the wavelet coefficients of affected regions to estimate the reflectivity values caused by these artifacts. By subtracting the estimated reflectivity values of the artifacts from the original reflectivity values, estimates of artifact reduced reflectivity values are attained. The improvements of our proposed method are substantiated by an evaluation of Field II simulated, in vivo mouse and human heart B mode images.

Small lesion detection with resolution enhancement compression

A novel coded-excitation method, resolution-enhancement compression (REC), increases the axial resolution and the echo signal-to-noise ratio (eSNR) for an ultrasonic imaging system. The REC technique was examined for its ability to improve lesion detectability. The REC technique was used to double the -3-dB fractional pulse-echo bandwidth of an ultrasonic source in both simulations and experiments. The increase in usable bandwidth increased lesion detectability compared to conventional pulsing (CP) techniques and coded excitation using a linear chirp (LC). Lesion detectibility was quantified through lesion signal-to-noise ratio (lSNR), which is a metric that quantifies the ability of an isolated observer to detect a focal lesion against a background. In simulations, a higher lSNR value was observed using the REC technique for lesions ranging in size from 1 mm to 8 mm in diameter. In addition, the eSNR was increased by almost 15 dB. To validate simulation results, a hydrogel-cone phantom was constructed to provide lesions with +6-dB contrast of different sizes. A transducer was scanned perpendicular to the major axis of the cone at different levels to provide lesions of 3, 5 and 8 mm in diameter. The lSNR was estimated for lesions of different sizes and using the three excitation techniques, i.e., CP, LC and REC. In experiments, the lSNR was observed to be higher using the REC technique than the other pulsing techniques. The lSNR scores for REC were higher by 15%, 45% and 40% for the 3, 5 and 8 mm over the other two excitation techniques. The eSNR was increased by 5.7 dB. Therefore, according to the lSNR metric, the improvement in spatial resolution from the REC technique resulted in improved detectability of small lesions.

Calibration of cross-sectional images measured by an ultrasound-based muscle evaluation system

The quantification of muscle volume can be used to estimate muscular strength. Therefore, we developed a flexible measuring system for muscle volume using ultrasonog-raphy. In the measuring process, subjects are not required to perform any muscular contraction, so it is completely safe and particularly suitable for elderly people. The ultrasound probe is installed on a mechanical arm, and continuously scans fragmental images along the body surface. The measured images are then composed into a wide area cross-sectional image. However, the muscle area measured by our system was slightly smaller than that measured by MRI. because the ultrasound probe contacted the body surface with a little pressure during the measurement. The strain then decreases the total image size and its circumference. This paper introduces our developed system and proposes a new calibration method for the muscle area in the thigh based on its circumference.

3-D spatial compounding using a row-column array

2-D spatial compounding has long been investigated to reduce speckle in ultrasound images. To further reduce speckle, several 3-D spatial compounding studies using 1-D and 1.5 D arrays with mechanical translation and position tracking have been reported. However, the fixed elevational focus and mechanical translation can degrade image quality in elevation. Using 2-D arrays, a better elevational resolution can be achieved with electronic focusing. Furthermore, 2-D arrays can generate greater number of independent images than 1-D arrays and the need for mechanical scanning is eliminated. In this paper, we present our 3-D spatial compounding images of two gel-based contrast phantoms and one resolution phantom. These images were acquired using a prototype 4 cm x 4 cm ultrasonic row-column prototype 2-D array operating at 5 MHz. Compounding nine decorrelated volumes showed a speckle signal-to-noise ratio (SNR) improvement of 2.68. The average improvement of the lesion contrast-to-noise ratio (CNR) was 2.45. However, using a smaller aperture to generate these volumes worsened the lateral resolution as predicted by theory.

Evaluating the robustness of dual apodization with cross-correlation

We have recently presented a new method to suppress side lobes and clutter in ultrasound imaging called dual apodization with cross-correlation (DAX). However, due to the random nature of speckle, artifactual black spots may arise with DAX-processed images. In this paper, we present one possible solution, called dynamic DAX, to reduce these black spots. We also evaluate the robustness of dynamic DAX in the presence of phase aberration and noise. Simulation results using a 5 MHz, 128-element linear array are presented using dynamic DAX with aberrator strengths ranging from 25 ns root-mean-square (RMS) to 45 ns RMS and correlation lengths of 3 mm and 5 mm. When simulating a 3 mm diameter anechoic cyst, at least 100% improvement in the contrast-to-noise ratio (CNR) compared with standard beamforming is seen using dynamic DAX, except in the most severe case. Layers of pig skin, fat, and muscle were used as experimental aberrators. Simulation and experimental results are also presented using dynamic DAX in the presence of noise. With a system signal-to-noise ratio (SNR) of at least 15 dB, we have a CNR improvement of more than 100% compared with standard beamforming. This work shows that dynamic DAX is able to improve the contrast-to-noise ratio reliably in the presence of phase aberration and noise.

Sidelobe suppression in ultrasound imaging using dual apodization with cross-correlation

This paper introduces a novel sidelobe and clutter suppression method in ultrasound imaging called dual apodization with cross-correlation or DAX. DAX dramatically improves the contrast-to-noise ratio (CNR) allowing for easier visualization of anechoic cysts and blood vessels. This technique uses dual apodization or weighting strategies that are effective in removing or minimizing clutter and efficient in terms of computational load and hardware/software needs. This dual apodization allows us to determine the amount of mainlobe versus clutter contribution in a signal by cross-correlating RF data acquired from 2 apodization functions. Simulation results using a 128 element 5 MHz linear array show an improvement in CNR of 139% compared with standard beamformed data with uniform apodization in a 3 mm diameter anechoic cylindrical cyst. Experimental CNR using a tissue-mimicking phantom with the same sized cyst shows an improvement of 123% in a DAX processed image.

Synthetic axial acquisition-full resolution, low-cost C-scan ultrasonic imaging

The synthetic axial acquisition (SAA) approach presented here is designed to produce C-scan images using low-cost, low bandwidth, front end electronics. We exploit plane wave transmission and shallow C-scan imaging of non-moving, or slowly moving, tissue regions. Between each transmit/receive cycle, the receive sampling trigger is offset by one sampling interval so that over a sequence of acquisitions a sufficiently long data record is synthesized to enable a high-quality approximation to conventional delay and sum beamforming. FIELD II simulations were performed to model the next generation of our sonic window C-scan imaging system using a 5 MHz center frequency, 50% bandwidth, and a 60x60 fully sampled two-dimensional (2- D) array with a 0.3-mm element pitch. These simulations, which include analysis of the impact of target motion both parallel and perpendicular to the acoustic beam, indicate that SAA is robust with respect to target motion no faster than 10 mm/s. The impact of electronic noise on SAA also is considered.

A portable measuring system for cross-sectional ultrasound images using spatial compounding and edge sharpening

This paper proposes a compensation for a blurred image caused by misregistration in spatial compounding. The edge sharpening based on morphological operations is applied to the compounded image. A portable measuring system of a cross-sectional ultrasound image is designed for measuring body composition. The system is developed for non-medical applications, for example, measurement of the volume of muscle and subcutaneous fat in lower extremities, upper extremities and abdomen for health care and sports science. A number of partially overlapping images that have been obtained from multiple angles are combined into a single compounded image. In experiment on human abdomen, the image quality was improved in speckle suppression and edge enhancement by using ensemble averaging and morphological edge sharpening. Resulting wide field-of-view image was sufficiently deblurred without emphasizing noise.

An ultrasound research interface for a clinical system

Under a contract with the National Cancer Institute, we have developed a research interface to an ultrasound system. This ultrasound research interface (URI) is an optional feature providing several basic capabilities not normally available on a clinical scanner. The URI can store high-quality beamformed radio-frequency data to file for off-line processing. Also, through an integrated user interface, the user is provided additional control over the B-mode receive aperture and color flow ensemble size. A third major capability is the ability to record and playback macro files. In this paper, we describe the URI and illustrate its use on three research examples: elastography, computed tomography, and spatial compounding.

An ultrasound research interface for a clinical system

Under a contract with the National Cancer Institute, we have developed a research interface to an ultrasound system. This ultrasound research interface (URI) is an optional feature providing several basic capabilities not normally available on a clinical scanner. The URI can store high-quality beamformed radio-frequency data to file for off-line processing. Also, through an integrated user interface, the user is provided additional control over the B-mode receive aperture and color flow ensemble size. A third major capability is the ability to record and playback macro files. In this paper, we describe the URI and illustrate its use on three research examples: elastography, computed tomography, and spatial compounding.

Efficient array beam forming by spatial filtering for ultrasound B-mode imaging

This paper proposes an efficient array beam-forming method using spatial matched filtering (SMF) for ultrasonic imaging. In the proposed method, ultrasonic waves are transmitted from an array subaperture with fixed transmit focus as in conventional array imaging. At receive, radio frequency echo signals from each receive channel are passed through a spatial matched filter that is constructed based on the system transmit-receive spatial impulse response. The filtered echo signals are then summed without time delays. The filter concentrates and spatially registers the echo energy from each element so that the pulse-echo impulse response of the summed output is focused with acceptably low side lobes. Analytical beam pattern analysis and simulation results using a linear array show that this spatial filtering method can improve lateral resolution and contrast-to-noise ratio as compared with conventional dynamic receive focusing (DRF) methods. Experimental results with a linear array are consistent but point out the need to address additional practical issues. Spatial filtering is equivalent to synthetic aperture methods that dynamically focus on both transmit and receive throughout the field of view. In one common example of phase aberrations, the SMF method was degraded to a degree comparable to conventional DRF methods.