Short-lag spatial coherence of backscattered echoes: imaging characteristics

Intrinsic Tradeoffs in Multi-Covariate Imaging of Sub-Resolution Targets

Multi-covariate Imaging of Sub-resolution Targets (MIST) is an estimation-based method of imaging the statistics of diffuse scattering targets. MIST estimates the contributions of a set of covariance models to the echo data covariance matrix. Models are defined based on a spatial decomposition of the theoretical transmit intensity distribution into ON-axis and OFF-axis contributions, delineated by a user-specified spatial cutoff. We define this cutoff as the region of interest width (ROI width). In our previous work, we selected the ROI width as the first zero crossing separating the mainlobe from the sidelobe regions. This article explores the effects of varying two key parameters on MIST image quality: 1) ROI width and 2) the degree of spatial averaging of the measured echo data covariance matrix. These results demonstrate a fundamental tradeoff between resolution and speckle texture. We characterize MIST imaging performance across these tunable parameters in a number of simulated, phantom, and in vivo liver applications. We consider performance in noise, fidelity to native contrast, resolution, and speckle texture. MIST is also compared with varying levels of spatial and frequency compounding, demonstrating quantitative improvements in image quality at comparable levels of speckle reduction. In an in vivo example, optimized MIST images demonstrated 20.2% and 13.4% improvements in contrast-to-noise ratio over optimized spatial and frequency compounding images, respectively. These results present a framework for selecting MIST parameters to maximize speckle signal-to-noise ratio without an appreciable loss in resolution.

The SVD Beamformer: Physical Principles and Application to Ultrafast Adaptive Ultrasound

A shift of paradigm is currently underway in biomedical ultrasound thanks to plane or diverging waves coherent compounding for faster imaging. One remaining challenge consists in handling phase and amplitude aberrations induced during the ultrasonic propagation through complex layers. Unlike conventional line-per-line imaging, ultrafast ultrasound provides backscattering information from the whole imaged area for each transmission. Here, we take benefit from this feature and propose an efficient approach to perform fast aberration correction. Our method is based on the Singular Value Decomposition (SVD) of an ultrafast compound matrix containing backscattered data for several plane wave transmissions. First, we explain the physical signification of SVD and associated singular vectors within the ultrafast matrix formalism. We theoretically demonstrate that the separation of spatial and angular variables, rendered by SVD on ultrafast data, provides an elegant and straightforward way to optimize the angular coherence of backscattered data. In heterogeneous media, we demonstrate that the first spatial and angular singular vectors retrieve respectively the non-aberrated image of a region of interest, and the phase and amplitude of its aberration law. Numerical, in vitro and in vivo results prove the efficiency of the image correction, but also the accuracy of the aberrator determination. Based on spatial and angular coherence, we introduce a complete methodology for adaptive beamforming of ultrafast data, performed on successive isoplanatism patches undergoing SVD beamforming. The simplicity of this method paves the way to real-time adaptive ultrafast ultrasound imaging and provides a theoretical framework for future quantitative ultrasound applications.

Lag-Based Filtered-Delay Multiply and Sum Beamformer Combined with Two Phase-Related Factors for Medical Ultrasound Imaging

A novel adaptive beamformer named filtered-delay multiply and sum (F-DMAS) has recently been proposed. Compared to the delay and sum (DAS) beamforming algorithm, F-DMAS can efficiently improve the resolution and contrast. However, the DAS can still be seen in the expansion of DMAS. Therefore, we rearrange the pair-wised signals in terms of lag in DMAS and then synthesize a lot of new signals. Thanks to the relationship between the spatial coherence and lag, these new signals can be thought of as sorted by the spatial coherence. Thus, we apply two phase-related factors, the polarity-based factor (PF) and the sign coherence factor (SCF), which are evaluated based on new signals, to weight the output of DMAS. The two approaches are consequently referred to as LAG-DMAS-PF and LAG-DMAS-SCF, respectively. The results show that, compared to F-DMAS and DAS, our proposed methods can improve the resolution and contrast to some extent without increasing too much computational complexity. In the comparison between LAG-DMAS-PF and LAG-DMAS-SCF, the latter has better performance, but the former can better protect image details.

Simulations and human cadaver head studies to identify optimal acoustic receiver locations for minimally invasive photoacoustic-guided neurosurgery

Real-time intraoperative guidance during minimally invasive neurosurgical procedures (e.g., endonasal transsphenoidal surgery) is often limited to endoscopy and CT-guided image navigation, which can be suboptimal at locating underlying blood vessels and nerves. Accidental damage to these critical structures can have severe surgical complications, including patient blindness and death. Photoacoustic image guidance was previously proposed as a method to prevent accidental injury. While the proposed technique remains promising, the original light delivery and sound reception components of this technology require alterations to make the technique suitable for patient use. This paper presents simulation and experimental studies performed with both an intact human skull (which was cleaned from tissue attachments) and a complete human cadaver head (with contents and surrounding tissue intact) in order to investigate optimal locations for ultrasound probe placement during photoacoustic imaging and to test the feasibility of a modified light delivery design. Volumetric x-ray CT images of the human skull were used to create k-Wave simulations of acoustic wave propagation within this cranial environment. Photoacoustic imaging of the internal carotid artery (ICA) was performed with this same skull. Optical fibers emitting 750 nm light were inserted into the nasal cavity for ICA illumination. The ultrasound probe was placed on three optimal regions identified by simulations: (1) nasal cavity, (2) ocular region, and (3) 1 mm-thick temporal bone (which received 9.2%, 4.7%, and 3.8% of the initial photoacoustic pressure, respectively, in simulations). For these three probe locations, the contrast of the ICA in comparative experimental photoacoustic images was 27 dB, 19 dB, and 12 dB, respectively, with delay-and-sum (DAS) beamforming and laser pulse energies of 3 mJ, 5 mJ, and 4.2 mJ, respectively. Short-lag spatial coherence (SLSC) beamforming improved the contrast of these DAS images by up to 15 dB, enabled visualization of multiple cross-sectional ICA views in a single image, and enabled the use of lower laser energies. Combined simulation and experimental results with the emptied skull and >1 mm-thick temporal bone indicated that the ocular and nasal regions were more optimal probe locations than the temporal ultrasound probe location. Results from both the same skull filled with ovine brains and eyes and the human cadaver head validate the ocular region as an optimal acoustic window for our current system setup, producing high-contrast (i.e., up to 35 dB) DAS and SLSC photoacoustic images within the laser safety limits of a novel, compact light delivery system design that is independent of surgical tools (i.e., a fiber bundle with 6.8 mm outer diameter, 2 mm-diameter optical aperture, and an air gap spacing between the sphenoid bone and fiber tips). These results are promising toward identifying, quantifying, and overcoming major system design barriers to proceed with future patient testing.

Incoherent Clutter Suppression Using Lag-One Coherence

The lag-one coherence (LOC), derived from the correlation between the nearest-neighbor channel signals, provides a reliable measure of clutter which, under certain assumptions, can be directly related to the signal-to-noise ratio of individual channel signals. This offers a direct means to decompose the beamsum output power into contributions from speckle and spatially incoherent noise originating from acoustic clutter and thermal noise. In this study, we applied a novel method called lag-one spatial coherence adaptive normalization (LoSCAN) to locally estimate and compensate for the contribution of spatially incoherent clutter from conventional delay-and-sum (DAS) images. Suppression of incoherent clutter by LoSCAN resulted in improved image quality without introducing many of the artifacts common to other adaptive imaging methods. In simulations with known targets and added channel noise, LoSCAN was shown to restore native contrast and increase DAS dynamic range by as much as 10-15 dB. These improvements were accompanied by DAS-like speckle texture along with reduced focal dependence and artifact compared with other adaptive methods. Under in vivo liver and fetal imaging conditions, LoSCAN resulted in increased generalized contrast-to-noise ratio (gCNR) in nearly all matched image pairs ( N = 366 ) with average increases of 0.01, 0.03, and 0.05 in good-, fair-, and poor-quality DAS images, respectively, and overall changes in gCNR from -0.01 to 0.20, contrast-to-noise ratio (CNR) from -0.05 to 0.34, contrast from -9.5 to -0.1 dB, and texture μ/σ from -0.37 to -0.001 relative to DAS.

Coherence-based quantification of acoustic clutter sources in medical ultrasound

The magnitudes by which aberration and incoherent noise sources, such as diffuse reverberation and thermal noise, contribute to degradations in image quality in medical ultrasound are not well understood. Theory predicting degradations in spatial coherence and contrast in response to combinations of incoherent noise and aberration levels is presented, and the theoretical values are compared to those from simulation across a range of magnitudes. A method to separate the contributions of incoherent noise and aberration in the spatial coherence domain is also presented and applied to predictions for losses in contrast. Results indicate excellent agreement between theory and simulations for beamformer gain and expected contrast loss due to incoherent noise and aberration. Error between coherence-predicted aberration contrast loss and measured contrast loss differs by less than 1.5 dB on average, for a -20 dB native contrast target and aberrators with a range of root-mean-square time delay errors. Results also indicate in the same native contrast target the contribution of aberration to contrast loss varies with channel signal-to-noise ratio (SNR), peaking around 0 dB SNR. The proposed framework shows promise to improve the standard by which clutter reduction strategies are evaluated.

A new method for assessing the performance of signal processing filters in suppressing the side lobe level

Purpose

This study aimed to propose a new ground truth ultrasound imaging method and to confirm its efficacy when applied to side lobe suppression filtering.

Methods

Using a computer simulation, we synthesized a side lobe-free image (i.e., with no side lobe whatsoever) by separating the main and side lobe signals in the construction of point target, speckled cyst, and pseudo-kidney images. During signal processing, we assessed the quality of the filtered image by comparing it with a ground truth image (i.e., the main lobe image).

Results

We examined the effect of reducing the side lobe by applying aperture apodization, side lobe estimation and reduction filtering, and minimum variance beamforming, which are widely used as side lobe suppression techniques. Despite the drawback of decreased resolution, the commonly used apodization method increases the contrast, which improves ultrasound image quality and enables a better diagnosis. Although side lobe estimation and reduction filtering and minimum variance beamforming are demanding in terms of computational resources, they can considerably improve ultrasound images. Compounding of ultrasound images processed by various signal processing methods increases the resolution and contrast, while reducing the speckle noise.

Conclusion

Although it appears that the proposed method can only be used for computer-generated radiofrequency data, this method can improve ultrasound image quality by identifying the characteristics of signal processing filters for side lobe suppression and applying appropriately adjusted filters to in vivo human imaging data.

GPU implementation of photoacoustic short-lag spatial coherence imaging for improved image-guided interventions

SIGNIFICANCE

Photoacoustic-based visual servoing is a promising technique for surgical tool tip tracking and automated visualization of photoacoustic targets during interventional procedures. However, one outstanding challenge has been the reliability of obtaining segmentations using low-energy light sources that operate within existing laser safety limits.

AIM

We developed the first known graphical processing unit (GPU)-based real-time implementation of short-lag spatial coherence (SLSC) beamforming for photoacoustic imaging and applied this real-time algorithm to improve signal segmentation during photoacoustic-based visual servoing with low-energy lasers.

APPROACH

A 1-mm-core-diameter optical fiber was inserted into ex vivo bovine tissue. Photoacoustic-based visual servoing was implemented as the fiber was manually displaced by a translation stage, which provided ground truth measurements of the fiber displacement. GPU-SLSC results were compared with a central processing unit (CPU)-SLSC approach and an amplitude-based delay-and-sum (DAS) beamforming approach. Performance was additionally evaluated with in vivo cardiac data.

RESULTS

The GPU-SLSC implementation achieved frame rates up to 41.2 Hz, representing a factor of 348 speedup when compared with offline CPU-SLSC. In addition, GPU-SLSC successfully recovered low-energy signals (i.e., ≤268  μJ) with mean ± standard deviation of signal-to-noise ratios of 11.2  ±  2.4 (compared with 3.5  ±  0.8 with conventional DAS beamforming). When energies were lower than the safety limit for skin (i.e., 394.6  μJ for 900-nm wavelength laser light), the median and interquartile range (IQR) of visual servoing tracking errors obtained with GPU-SLSC were 0.64 and 0.52 mm, respectively (which were lower than the median and IQR obtained with DAS by 1.39 and 8.45 mm, respectively). GPU-SLSC additionally reduced the percentage of failed segmentations when applied to in vivo cardiac data.

CONCLUSIONS

Results are promising for the use of low-energy, miniaturized lasers to perform GPU-SLSC photoacoustic-based visual servoing in the operating room with laser pulse repetition frequencies as high as 41.2 Hz.

Application of the generalized contrast-to-noise ratio to assess photoacoustic image quality

The generalized contrast-to-noise ratio (gCNR) is a relatively new image quality metric designed to assess the probability of lesion detectability in ultrasound images. Although gCNR was initially demonstrated with ultrasound images, the metric is theoretically applicable to multiple types of medical images. In this paper, the applicability of gCNR to photoacoustic images is investigated. The gCNR was computed for both simulated and experimental photoacoustic images generated by amplitude-based (i.e., delay-and-sum) and coherence-based (i.e., short-lag spatial coherence) beamformers. These gCNR measurements were compared to three more traditional image quality metrics (i.e., contrast, contrast-to-noise ratio, and signal-to-noise ratio) applied to the same datasets. An increase in qualitative target visibility generally corresponded with increased gCNR. In addition, gCNR magnitude was more directly related to the separability of photoacoustic signals from their background, which degraded with the presence of limited bandwidth artifacts and increased levels of channel noise. At high gCNR values (i.e., 0.95-1), contrast, contrast-to-noise ratio, and signal-to-noise ratio varied by up to 23.7-56.2 dB, 2.0-3.4, and 26.5-7.6×10²⁰, respectively, for simulated, experimental phantom, and in vivo data. Therefore, these traditional metrics can experience large variations when a target is fully detectable, and additional increases in these values would have no impact on photoacoustic target detectability. In addition, gCNR is robust to changes in traditional metrics introduced by applying a minimum threshold to image amplitudes. In tandem with other photoacoustic image quality metrics and with a defined range of 0 to 1, gCNR has promising potential to provide additional insight, particularly when designing new beamformers and image formation techniques and when reporting quantitative performance without an opportunity to qualitatively assess corresponding images (e.g., in text-only abstracts).

MimickNet, Mimicking Clinical Image Post- Processing Under Black-Box Constraints

Image post-processing is used in clinical-grade ultrasound scanners to improve image quality (e.g., reduce speckle noise and enhance contrast). These post-processing techniques vary across manufacturers and are generally kept proprietary, which presents a challenge for researchers looking to match current clinical-grade workflows. We introduce a deep learning framework, MimickNet, that transforms conventional delay-and-summed (DAS) beams into the approximate Dynamic Tissue Contrast Enhanced (DTCE™) post-processed images found on Siemens clinical-grade scanners. Training MimickNet only requires post-processed image samples from a scanner of interest without the need for explicit pairing to DAS data. This flexibility allows MimickNet to hypothetically approximate any manufacturer's post-processing without access to the pre-processed data. MimickNet post-processing achieves a 0.940 ± 0.018 structural similarity index measurement (SSIM) compared to clinical-grade post-processing on a 400 cine-loop test set, 0.937 ± 0.025 SSIM on a prospectively acquired dataset, and 0.928 ± 0.003 SSIM on an out-of-distribution cardiac cine-loop after gain adjustment. To our knowledge, this is the first work to establish deep learning models that closely approximate ultrasound post-processing found in current medical practice. MimickNet serves as a clinical post-processing baseline for future works in ultrasound image formation to compare against. Additionally, it can be used as a pretrained model for fine-tuning towards different post-processing techniques. To this end, we have made the MimickNet software, phantom data, and permitted in vivo data open-source at https://github.com/ouwen/MimickNet.

Synthetic Aperture Focusing for Multi-Covariate Imaging of Sub-Resolution Targets

Coherence-based imaging methods suffer from reduced image quality outside the depth of field for focused ultrasound transmissions. Synthetic aperture methods can extend the depth of field by coherently compounding time-delayed echo data from multiple transmit events. Recently, our group has presented the Multi-covariate Imaging of Sub-resolution Targets (MIST), an estimation-based method to image the statistical properties of diffuse targets. MIST has demonstrated improved image quality over conventional delay-and-sum, but like many coherence-based imaging methods, suffers from limited depth of field artifacts. This article applies synthetic aperture focusing to MIST, which is evaluated using focused, plane-wave, and diverging-wave transmit geometries. Synthetic aperture MIST is evaluated in simulation, phantom, and in vivo applications, demonstrating consistent improvements in contrast-to-noise ratio (CNR) over conventional dynamic receive MIST outside the transmit depth of field, with approximately equivalent results between synthetic transmit geometries. In vivo synthetic aperture MIST images demonstrated 16.8 dB and 16.6% improvements in contrast and CNR, respectively, over dynamic receive MIST images, as well as 17.4 dB and 32.3% improvements over synthetic aperture B-Mode. MIST performance is characterized in the space of plane-wave imaging, where the total plane-wave count is reduced through coarse angular sampling or total angular span. Simulation and experimental results indicate wide applicability of MIST to synthetic aperture imaging methods.

Coherence-Based Beamforming Increases the Diagnostic Certainty of Distinguishing Fluid from Solid Masses in Breast Ultrasound Exams

Ultrasound is often used as a supplement for mammography to detect breast cancer. However, one known limitation is the high false-positive rates associated with breast ultrasound. We investigated the use of coherence-based beamforming (which directly displays spatial coherence) as a supplement to standard ultrasound B-mode images in 25 patients recommended for biopsy (26 masses in total), with the eventual goal of decreasing false-positive rates. Because of the coherent signal present within solid masses, coherence-based beamforming methods allow solid and fluid-filled masses to appear significantly different (p < 0.001). When presented to five board-certified radiologists, the inclusion of robust short-lag spatial coherence (R-SLSC) images in the diagnostic pipeline reduced the uncertainty of fluid-filled mass contents from 47.5% to 15.8% and reduced the percentage of fluid-filled masses unnecessarily recommended for biopsy from 43.3% to 13.3%. These results are promising for the potential introduction of R-SLSC (and related coherence-based beamforming methods) into the breast clinic to improve diagnostic certainty and reduce the number of unnecessary biopsies.

A Spatial Coherence Beamformer Design for Power Doppler Imaging

Acoustic clutter is a primary source of image degradation in ultrasound imaging. In the context of flow imaging, tissue and acoustic clutter signals are often much larger in magnitude than the blood signal, which limits the sensitivity of conventional power Doppler in SNR-limited environments. This has motivated the development of coherence-based beamformers, including Coherent Flow Power Doppler (CFPD), which have demonstrated efficacy in mitigating sources of diffuse clutter. However, CFPD uses a measure of normalized coherence, which incurs a non-linear relationship between image intensity and the magnitude of the blood echo. As a result, CFPD is not a robust approach to study gradation of blood signal energy, which depicts the fractional moving blood volume. We propose the application of mutual intensity, rather than normalized coherence, to retain the clutter suppression capability inherent in coherence beamforming, while preserving the underlying signal energy. Feasibility of this approach was shown via Field II simulations, phantoms, and in vivo human liver data. In addition, we derive an adaptive statistical threshold for the suppression of residual noise signals. Overall, this beamformer design shows promise as an alternative technique to depict flow volume gradation in cluttered imaging environments.

The Generalized Contrast-to-Noise Ratio: A Formal Definition for Lesion Detectability

In the last 30 years, the contrast-to-noise ratio (CNR) has been used to estimate the contrast and lesion detectability in ultrasound images. Recent studies have shown that the CNR cannot be used with modern beamformers, as dynamic range alterations can produce arbitrarily high CNR values with no real effect on the probability of lesion detection. We generalize the definition of CNR based on the overlap area between two probability density functions. This generalized CNR (gCNR) is robust against dynamic range alterations; it can be applied to all kind of images, units, or scales; it provides a quantitative measure for contrast; and it has a simple statistical interpretation, i.e., the success rate that can be expected from an ideal observer at the task of separating pixels. We test gCNR on several state-of-the-art imaging algorithms and, in addition, on a trivial compression of the dynamic range. We observe that CNR varies greatly between the state-of-the-art methods, with improvements larger than 100%. We observe that trivial compression leads to a CNR improvement of over 200%. The proposed index, however, yields the same value for compressed and uncompressed images. The tested methods showed mismatched performance in terms of lesion detectability, with variations in gCNR ranging from -0.08 to +0.29. This new metric fixes a methodological flaw in the way we study contrast and allows us to assess the relevance of new imaging algorithms.

In Vivo Demonstration of Photoacoustic Image Guidance and Robotic Visual Servoing for Cardiac Catheter-Based Interventions

Cardiac interventional procedures are often performed under fluoroscopic guidance, exposing both the patient and operators to ionizing radiation. To reduce this risk of radiation exposure, we are exploring the use of photoacoustic imaging paired with robotic visual servoing for cardiac catheter visualization and surgical guidance. A cardiac catheterization procedure was performed on two in vivo swine after inserting an optical fiber into the cardiac catheter to produce photoacoustic signals from the tip of the fiber-catheter pair. A combination of photoacoustic imaging and robotic visual servoing was employed to visualize and maintain constant sight of the catheter tip in order to guide the catheter through the femoral or jugular vein, toward the heart. Fluoroscopy provided initial ground truth estimates for 1D validation of the catheter tip positions, and these estimates were refined using a 3D electromagnetic-based cardiac mapping system as the ground truth. The 1D and 3D root mean square errors ranged 0.25-2.28 mm and 1.24-1.54 mm, respectively. The catheter tip was additionally visualized at three locations within the heart: (1) inside the right atrium, (2) in contact with the right ventricular outflow tract, and (3) inside the right ventricle. Lasered regions of cardiac tissue were resected for histopathological analysis, which revealed no laser-related tissue damage, despite the use of 2.98 mJ per pulse at the fiber tip (379.2 mJ/cm² fluence). In addition, there was a 19 dB difference in photoacoustic signal contrast when visualizing the catheter tip pre- and post-endocardial tissue contact, which is promising for contact confirmation during cardiac interventional procedures (e.g., cardiac radiofrequency ablation). These results are additionally promising for the use of photoacoustic imaging to guide cardiac interventions by providing depth information and enhanced visualization of catheter tip locations within blood vessels and within the beating heart.

A United Sign Coherence Factor Beamformer for Coherent Plane-Wave Compounding with Improved Contrast

In this study, we present a united sign coherence factor beamformer for coherent plane-wave compounding (CPWC). CPWC is capable of reaching an image quality comparable to the conventional B-mode with a much higher frame rate. Conventional coherence factor (CF) based beamformers for CPWC are based on one-dimensional (1D) frameworks, either in the spatial coherence dimension or angular coherence dimension. Both 1D frameworks do not take into account the coherence information of the dimensions of each other. In order to take full advantage of the radio-frequency (RF) data, this paper proposes a united framework containing both spatial and angular information for CPWC. A united sign coherence factor beamformer (uSCF), which combines the conventional sign coherence factor (SCF) and the united framework, is introduced in the paper as well. The proposed beamformer is compared with the conventional 1D SCF beamformers (spatial and angular dimension beamformers) using simulation, phantom and in vivo studies. In the in vivo images, the proposed method improves the contrast ratio (CR) and generalized contrast-to-noise ratio (gCNR) by 197% and 20% over CPWC. Compared with other 1D methods, uSCF also shows an improved contrast and lateral resolution on all datasets.

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.

A Comparison of Coherence-Based Beamforming Techniques in High-Frame-Rate Ultrasound Imaging With Multi-Line Transmission

One of the current challenges in ultrasound imaging is achieving higher frame rates, particularly in cardiac applications, where tracking the heart motion and other rapid events can provide potential valuable diagnostic information. The main drawback of ultrasound high-frame-rate strategies is that usually they partly sacrifice image quality in order to speed up the acquisition time. In particular, multi-line transmission (MLT), which consists in transmitting multiple ultrasound beams simultaneously in different directions, has been proven able to improve frame rates in echocardiography, unfortunately generating artifacts due to inter-beam crosstalk interferences. This work investigates the possibility to effectively suppress crosstalk artifacts in MLT while improving image quality by applying beamforming techniques based on backscattered signals spatial coherence. Several coherence-based algorithms (i.e., short-lag filtered-delay multiply and sum beamforming, coherence and generalized coherence factor, phase and sign coherence, and nonlinear beamforming with p th root compression) are implemented and compared, and their performance trends are evaluated when varying their design parameters. Indeed, experimental results of phantom and in vivo cardiac acquisitions demonstrate that this class of algorithms can provide significant benefits compared with delay and sum, well-suppressing artifacts (up to 48.5-dB lower crosstalk), and increasing image resolution (by up to 46.3%) and contrast (by up to 30 dB in terms of contrast ratio and 12.6% for generalized contrast-to-noise ratio) at the same time.

An adaptive imaging method for ultrasound coherent plane-wave compounding based on the subarray zero-cross factor

Coherent plane-wave compounding (CPWC) has the ability to generate high quality image using the backscattered signals from plane wave emitting at different steer angles. To improve the image quality of CPWC, adaptive weighting techniques have been introduced in the compounding procedure. This paper proposes subarray zeros-cross factor (SZF) for CPWC, and it is used as an adaptive weighting factor to improve image quality. The SZF is calculated based on polarity of plane-wave imaging results with adjacent steering angle to estimate the coherence of plane wave emitting events. It is effective to suppress noise and maintain background speckle pattern. Simulations and experiments were conducted to evaluate the performance of the proposed method. Results demonstrate that the SZF can achieve better performance on contrast ratio (CR) and resolution than traditional CPWC. For simulated cysts, a maximal CR improvement of 125.4% is achieved. For experimental cysts, the maximal CR improvement is 197.9%. Compared with coherence factor (CF) and generalized coherence factor (GCF), SZF can obtain improvements in contrast-to-noise ratio and speckle signal-to-noise ratio at near field and increase CR at far field. In addition, when subarray length L is in the range of [10,12], SZF can obtain satisfying comprehensive performance.

High-Frame-Rate Tri-Plane Echocardiography With Spiral Arrays: From Simulation to Real-Time Implementation

Major cardiovascular diseases (CVDs) are associated with (regional) dysfunction of the left ventricle. Despite the 3-D nature of the heart and its dynamics, the assessment of myocardial function is still largely based on 2-D ultrasound imaging, thereby making diagnosis heavily susceptible to the operator's expertise. Unfortunately, to date, 3-D echocardiography cannot provide adequate spatiotemporal resolution in real-time. Hence, tri-plane imaging has been introduced as a compromise between 2-D and true volumetric ultrasound imaging. However, tri-plane imaging typically requires high-end ultrasound systems equipped with fully populated matrix array probes embedded with expensive and little flexible electronics for two-stage beamforming. This article presents an advanced ultrasound system for real-time, high frame rate (HFR), and tri-plane echocardiography based on low element count sparse arrays, i.e., the so-called spiral arrays. The system was simulated, experimentally validated, and implemented for real-time operation on the ULA-OP 256 system. Five different array configurations were tested together with four different scan sequences, including multi-line and planar diverging wave transmission. In particular, the former can be exploited to achieve, in tri-plane imaging, the same temporal resolution currently used in clinical 2-D echocardiography, at the expenses of contrast (-3.5 dB) and signal-to-noise ratio (SNR) (-8.7 dB). On the other hand, the transmission of planar diverging waves boosts the frame rate up to 250 Hz, but further compromises contrast (-10.5 dB), SNR (-9.7 dB), and lateral resolution (+46%). In conclusion, despite an unavoidable loss in image quality and sensitivity due to the limited number of elements, HFR tri-plane imaging with spiral arrays is shown to be feasible in real-time and may enable real-time functional analysis of all left ventricular segments of the heart.

A dynamic generalized coherence factor for side lobe suppression in ultrasound imaging

Coherence-based weighting techniques have been widely studied to weight beamsummed data to improve image quality in ultrasound imaging. Although generalized coherence factor (GCF) enhances the robustness of coherence factor (CF) with preserved speckle pattern by including some incoherent components, the side lobe suppression performance is insufficient due to constant cut-off frequency M₀. To address this problem, we introduced in this paper a dynamic GCF method, referred to as DGCF-C, based on the amplitude standard deviation and the convolution output of aperture data. The cut-off frequency is adaptively selected for GCF at each imaging point using the amplitude standard deviation of aperture data. Moreover, the convolution output of aperture data is used to calculate the dynamic GCF. The proposed method is evaluated in simulation and tissue-mimicking phantom studies. The image quality was analyzed in terms of resolution, contrast ratio (CR), generalized contrast-to-noise ratio (GCNR), speckle signal-to-noise ratio (sSNR), and signal-to-noise ratio (SNR). The results demonstrate that DGCF-C (M_max=2) achieves mean resolution improvements of 35.1% in simulation, and 32.6% in experiment, compared with GCF (M₀=1). Moreover, DGCF-C (M_max=4) outperforms GCF (M₀=2) with an average GCNR improvement of 13.5% and an average sSNR improvement of 15.2%, which indicates the better-preservation of speckle.

Combining autocorrelation signals with delay multiply and sum beamforming algorithm for ultrasound imaging

Beamformer is one of the most important components in ultrasound imaging system. The delay and sum (DAS) beamforming algorithm has been widely used in recent decades due to its simplicity and robustness. However, it has poor impact on resolution and contrast. A new beamformer named filtered delay multiply and sum (F-DMAS) which was an alternative of delay multiply and sum (DMAS) was proposed to overcome these shortcomings of DAS. Although F-DMAS partially enhances the image quality, its performance still has room for improvement. Therefore, a novel beamformer named lag-based delay multiply and sum (L-DMAS) which combines autocorrelation signals with DMAS algorithm is proposed by us to improve its efficiency. Field II was employed to synthesize a point target phantom and a cyst phantom to compare the performance between DAS, F-DMAS, double stage delay multiply and sum (DS-DMAS), and L-DMAS. We also estimate the performance of four algorithms on experimental data and in vivo data. These results show that both DS-DMAS and L-DMAS are better than DAS and F-DMAS in each case. In some cases, DS-DMAS and L-DMAS have little difference in performance, but in other cases, L-DMAS outperforms DS-DMAS. Graphical Abstract.

Computationally Efficient Implementation of Aperture Domain Model Image Reconstruction

Aperture domain model image reconstruction (ADMIRE) is a useful tool to mitigate ultrasound imaging artifacts caused by acoustic clutter. However, its lengthy run-time impairs its usefulness. To overcome this drawback, we evaluated the reduced model methods with otherwise similar performance to ADMIRE. We also assessed other approaches to speed up ADMIRE, including the use of different levels of short-time Fourier transform (STFT) window overlap and examining the degrees of freedom of the model fit. In this study, we conducted an analysis of the reduced models, including those using Gram-Schmidt orthonormalization (GSO), singular value decomposition (SVD), and independent component analysis (ICA). We evaluated these reduced models using the data from simulations, experimental phantoms, and in vivo liver scans. We then tested ADMIRE's performance using full, GSO, SVD, and ICA-fourth-order blind identification (ICA-FOBI) models. The results from simulations, experimental phantoms, and in vivo data indicate that a model reduced using the ICA-FOBI method is the most promising for accelerating ADMIRE implementation. In the in vivo liver data, the improvements in contrast relative to delay-and-sum (DAS) using a full model, GSO, SVD, and ICA-FOBI models are 6.29 ± 0.25 dB, 11.88 ± 0.90 dB, 9.01 ± 0.67 dB, and 6.36 ± 0.27 dB, respectively; whereas, the contrast-to-noise ratio (CNR) improvement values in the same order are 0.04 ± 0.06 dB, -1.70 ± 0.17 dB, -1.51 ± 0.19 dB, and 0.12 ± 0.07 dB, respectively. The implementation of ADMIRE using the reduced model methods can decrease ADMIRE's computational complexity over three orders of magnitude. The use of a 50% STFT window overlap reduces ADMIRE's serial run time by more than one order of magnitude without any remarkable loss of image quality, when compared to the use of a 90% window overlap used previously. Based on these findings, a combination of the ICA-FOBI model and the use of a 50% STFT window overlap makes the ADMIRE algorithm more computationally efficient.

Two-Dimensional Spatial Coherence for Ultrasonic DMAS Beamforming in Multi-Angle Plane-Wave Imaging

Ultrasonic multi-angle plane-wave (PW) coherent compounding relies on delay-and-sum (DAS) beamforming of two-dimensional (2D) echo matrix in both the dimensions PW transmit angle and receiving channel to construct each image pixel. Due to the characteristics of DAS beamforming, PW coherent compounding may suffer from high image clutter when the number of transmit angles is kept low for ultrafast image acquisition. Delay-multiply-and-sum (DMAS) beamforming exploits the spatial coherence of the receiving aperture to suppress clutter interference. Previous attempts to introduce DMAS beamforming into multi-angle PW imaging has been reported but only in either dimension of the 2D echo matrix. In this study, a novel DMAS operation is proposed to extract the 2D spatial coherence of echo matrix for further improvement of image quality. The proposed 2D-DMAS method relies on a flexibly tunable p value to manipulate the signal coherence in the beamforming output. For p = 2.0 as an example, simulation results indicate that 2D-DMAS outperforms other one-dimensional DMAS methods by at least 9.3 dB in terms of ghost-artifact suppression. Experimental results also show that 2D-DMAS provides the highest improvement in lateral resolution by 32% and in image contrast by 15.6 dB relative to conventional 2D-DAS beamforming. Nonetheless, since 2D-DMAS emphasizes signal coherence more than its one-dimensional DMAS counterparts, it suffers from the most elevated speckle variation and the granular pattern in the tissue background.

Non-contrast power Doppler ultrasound imaging for early assessment of trans-arterial chemoembolization of liver tumors

Trans-arterial chemoembolization (TACE) is an important yet variably effective treatment for management of hepatic malignancies. Lack of response can be in part due to inability to assess treatment adequacy in real-time. Gold-standard contrast enhanced computed tomography and magnetic resonance imaging, although effective, suffer from treatment-induced artifacts that prevent early treatment evaluation. Non-contrast ultrasound is a potential solution but has historically been ineffective at detecting treatment response. Here, we propose non-contrast ultrasound with recent perfusion-focused advancements as a tool for immediate evaluation of TACE. We demonstrate initial feasibility in an 11-subject pilot study. Treatment-induced changes in tumor perfusion are detected best when combining adaptive demodulation (AD) and singular value decomposition (SVD) techniques. Using a 0.5 s (300-sample) ensemble size, AD + SVD resulted in a 7.42 dB median decrease in tumor power after TACE compared to only a 0.06 dB median decrease with conventional methods.

Speckle coherence of piecewise-stationary stochastic targets

The van Cittert-Zernike (VCZ) theorem describes the propagation of spatial covariance from an incoherent source distribution, such as backscatter from stochastic targets in pulse-echo imaging. These stochastic targets are typically assumed statistically stationary and spatially incoherent with uniform scattering strength. In this work, the VCZ theorem is applied to a piecewise-stationary scattering model. Under this framework, the spatial covariance of the received echo data is demonstrated as the linear superposition of covariances from distinct spatial regions. This theory is analytically derived from fundamental physical principles, and validated through simulation studies demonstrating superposition and scaling. Simulations show that linearity is preserved over various depths and transmit apodizations, and in the presence of noise. These results provide a general framework to decompose spatial covariance into contributions from distinct regions of interest, which may be applied to advanced imaging methods. While the simulation tools used for validation are specific to ultrasound, this analysis is generally applicable to other coherent imaging applications involving stochastic targets. This covariance decomposition provides the physical basis for a recently described imaging method, Multi-covariate Imaging of Sub-resolution Targets.

Streak artifact suppression in photoacoustic computed tomography using adaptive back projection

For photoacoustic computed tomography (PACT), an insufficient number of ultrasound detectors can cause serious streak-type artifacts. These artifacts get overlaid on top of image features, and thus locally jeopardize image quality and resolution. Here, a reconstruction algorithm, termed Contamination-Tracing Back-Projection (CTBP), is proposed for the mitigation of streak-type artifacts. During reconstruction, CTBP adaptively adjusts the back-projection weight, whose value is determined by the likelihood of contamination, to minimize the negative influences of strong absorbers. An iterative solution of the eikonal equation is implemented to accurately trace the time of flight of different pixels. Numerical, phantom and in vivo experiments demonstrate that CTBP can dramatically suppress streak artifacts in PACT and improve image quality.

In vivo photoacoustic imaging of major blood vessels in the pancreas and liver during surgery

Abdominal surgeries carry considerable risk of gastrointestinal and intra-abdominal hemorrhage, which could possibly cause patient death. Photoacoustic imaging is one solution to overcome this challenge by providing visualization of major blood vessels during surgery. We investigate the feasibility of in vivo blood vessel visualization for photoacoustic-guided liver and pancreas surgeries. In vivo photoacoustic imaging of major blood vessels in these two abdominal organs was successfully achieved after a laparotomy was performed on two swine. Three-dimensional photoacoustic imaging with a robot-controlled ultrasound (US) probe and color Doppler imaging were used to confirm vessel locations. Blood vessels in the in vivo liver were visualized with energies of 20 to 40 mJ, resulting in 10 to 15 dB vessel contrast. Similarly, an energy of 36 mJ was sufficient to visualize vessels in the pancreas with up to 17.3 dB contrast. We observed that photoacoustic signals were more focused when the light source encountered a major vessel in the liver. This observation can be used to distinguish major blood vessels in the image plane from the more diffuse signals associated with smaller blood vessels in the surrounding tissue. A postsurgery histopathological analysis was performed on resected pancreatic and liver tissues to explore possible laser-related damage. Results are generally promising for photoacoustic-guided abdominal surgery when the US probe is fixed and the light source is used to interrogate the surgical workspace. These findings are additionally applicable to other procedures that may benefit from photoacoustic-guided interventional imaging of the liver and pancreas (e.g., biopsy and guidance of radiofrequency ablation lesions in the liver).

Coherent Multi-Transducer Ultrasound Imaging

This work extends the effective aperture size by coherently compounding the received radio frequency data from multiple transducers. As a result, it is possible to obtain an improved image, with enhanced resolution, an extended field of view (FoV), and high-acquisition frame rates. A framework is developed in which an ultrasound imaging system consisting of N synchronized matrix arrays, each with partly shared FoV, take turns to transmit plane waves (PWs). Only one individual transducer transmits at each time while all N transducers simultaneously receive. The subwavelength localization accuracy required to combine information from multiple transducers is achieved without the use of any external tracking device. The method developed in this study is based on the study of the backscattered echoes received by the same transducer and resulting from a targeted scatterer point in the medium insonated by the multiple ultrasound probes of the system. The current transducer locations along with the speed of sound in the medium are deduced by optimizing the cross correlation between these echoes. The method is demonstrated experimentally in 2-D for two linear arrays using point targets and anechoic lesion phantoms. The first demonstration of a free-hand experiment is also shown. Results demonstrate that the coherent multi-transducer ultrasound imaging method has the potential to improve ultrasound image quality, improving resolution, and target detectability. Compared with coherent PW compounding using a single probe, lateral resolution improved from 1.56 to 0.71 mm in the coherent multi-transducer imaging method without acquisition frame rate sacrifice (acquisition frame rate 5350 Hz).

Efficient Transmit Delay Calculation in Ultrasound Coherent Plane-Wave Compound Imaging for Curved Array Transducers

The recently introduced plane-wave compounding method based on multiple plane-wave excitation has enabled several new applications due to its high frame rate (>1000 Hz). In this paper, a new efficient transmit delay calculation method in plane-wave compound imaging for a curved array transducer is presented. In the proposed method, the transmit delay is only calculated for a steering angle of 0° and is shifted along the element of the transducer to obtain other transmit delays for different steering angles. To evaluate the performance of the proposed method, the computational complexity was measured for various transmission conditions. For the number of elements and plane-wave excitations of 128 and 65, respectively, the number of operations was substantially decreased in the proposed method compared with the conventional method (256 vs. 8320). The benefits of the proposed method were demonstrated with phantom and in vivo experiments, where coherent plane-wave compounding with 65 excitations provided larger CR and CNR values compared to nine excitations (−22.5 dB and 2.7 vs. −11.3 dB and 1.9, respectively). These results indicate the proposed method can effectively reduce the computational complexity for plane-wave compound imaging in curved array transducers.

Multi-covariate Imaging of Sub-resolution Targets

Conventional B-mode ultrasound imaging assumes that targets consist of collections of point scatterers. Diffraction, however, presents a fundamental limit on a scanner's ability to resolve individual scatterers in most clinical imaging environments. Well-known optics and ultrasound literature has characterized these diffuse scattering targets as spatially incoherent and statistically stationary. In this paper, we apply a piecewise-stationary statistical model to diffuse scattering targets, in which the covariance of backscattered echoes can be described as the linear superposition of constituent components corresponding to echoes from distinct spatial regions in the field. Using this framework, we present Multi-covariate Imaging of Sub-resolution Targets (MIST), a novel estimation-based method to image the statistical properties of diffuse scattering targets, based on a decomposition of aperture domain spatial covariance. The mathematical foundations of the estimator are analytically derived, and MIST is evaluated in phantom, simulation, and in vivo studies, demonstrating consistent improvements in contrast-to-noise ratio and speckle statistics across imaging targets, without an apparent loss in resolution.

Ultrasound Baseband Delay-Multiply-and-Sum (BB-DMAS) nonlinear beamforming

Compared to conventional Delay-and-Sum (DAS) beamforming, Delay-Multiply-and-Sum (DMAS) imaging uses multiplicative coupling of channel pairs for spatial coherence of receiving aperture to improve image resolution and contrast. However, present DMAS imaging is based on the radio-frequency (RF) channel signals (RF-DMAS) and thus requires large oversampling to avoid aliasing and switching of band-pass filtering to isolate the corresponding spectral components for imaging. Baseband DMAS (BB-DMAS) beamforming in this study is based on the demodulated channel signals to provide similar results but with simplified signal processing. The BB-DMAS beamforming scales the magnitude of time-delayed channel signal by p-th root while maintaining the phase. After channel sum, the output dimensionality is restored by p-th power. The multiplicative coupling in BB-DMAS always renders baseband signal and thus the need for oversampling is eliminated. Besides, the BB-DMAS can use any rational p values to provide flexible image quality and an explicit relation between BB-DMAS beamforming and channel-domain phase coherence exists. Our results show that the image characteristics between BB-DMAS and RF-DMAS are similar. The suppression of lateral side lobe level, grating lobe level and uncorrelated random noises gradually increases with the rational p value in BB-DMAS beamforming. The image contrast improves from -24.8 dB in DAS to -34.3 dB, -43.0 dB and -51.4 dB in BB-DMAS, respectively with p value of 1.5, 2.0 and 2.5. In conclusion, BB-DMAS beamforming provides flexible manipulation of image quality by introducing baseband spatial coherence in the ultrasonic imaging.

Multi-line acquisition with delay multiply and sum beamforming in phased array ultrasound imaging, validation of simulation and in vitro

Increasing the frame rate of medical ultrasound imaging is very important, especially in applications such as cardiac diagnostic imaging, where such an imaging should be able to facilitate the examination of the temporal behaviour of the short cardiac cycle. Frame rate can be increased by the multi-line acquisition (MLA) method, also called parallel receive beamforming (PRB), where several beams are received from a single transmit (Tx) beam. The shortage is that imaging performance would be sacrificed. Filtered-delay multiply and sum (F-DMAS) is a non-linear beamforming technique proven to be able to improve the contrast and resolution of the image compared to traditional delay and sum (DAS) beamforming. In this paper, we proposed to combine MLA and the lower complexity F-DMAS algorithm, and use synthetic transmit beams (STB) to reduce the artifacts of MLA. The simulations of point targets and cyst phantoms were all carried out in Matlab using Field II. The results show that 2 line acquisition with delay multiply and sum (DMAS 2MLA) beamforming presents an equivalent imaging performance to that of traditional DMAS beamforming, and obtains a 7.69% higher resolution and 2 times higher contrast ratio in comparison to DAS beamforming. A real RF data experiment was applied to support the feasibility and validity of our method. The low complexity of F-DMAS (O(N)) would make it easy to implement 2 parallel beamformers. Thus, by combining 2MLA and F-DMAS, the frame rate can be improved to 2-fold higher with a better image quality compared to that of DAS beamforming.

Studying the Origin of Reverberation Clutter in Echocardiography: In Vitro Experiments and In Vivo Demonstrations

Clutter in echocardiography hinders the visualization of the heart and reduces the diagnostic value of the images. The detailed mechanisms that generate clutter are, however, not well understood. We present five different hypotheses for generation of clutter based on reverberation artifact with a focus on apical four-chamber view echocardiograms. We demonstrate the plausibility of our hypotheses by in vitro experiments and by comparing the results with in vivo recordings from four volunteers. The results show that clutter in echocardiography can be originated both at structures that lie in the ultrasound beam path and at those that are outside the imaging plane. We show that reverberations from echogenic structures outside the imaging plane can make clutter over the image if the ultrasound beam gets deflected out of its intended path by specular reflection at the ribs. Different clutter types in the in vivo examples show that the appearance of clutter varies, depending on the tissue from which it originates. The results of this work can be applied to improve clutter reduction techniques or to design ultrasound transducers that give higher quality cardiac images. The results can also help cardiologists have a better understanding of clutter in echocardiograms and acquire better images based on the type and the source of the clutter.

The Effect of Dynamic Range Alterations in the Estimation of Contrast

Many adaptive beamformers claim to produce images with increased contrast, a feature that could enable a better detection of lesions and anatomical structures. Contrast is often quantified using the contrast ratio (CR) and the contrast-to-noise ratio (CNR). The estimation of CR and CNR can be affected by dynamic range alterations (DRAs), such as those produced by a trivial gray-level transformation. Thus, we can form the hypothesis that contrast improvements from adaptive beamformers can, partly, be due to DRA. In this paper, we confirm this hypothesis. We show evidence on the influence of DRA on the estimation of CR and CNR and on the fact that several methods in the state of the art do alter the DR. To study this phenomenon, we propose a DR test (DRT) to estimate the degree of DRA and we apply it to seven beamforming methods. We show that CR improvements correlate with DRT with [Formula: see text] in simulated data and [Formula: see text] in experiments. We also show that DRA may lead to increased CNR values, under some circumstances. These results suggest that claims on lesion detectability, based on CR and CNR values, should be revised.

Combining Slow Flow Techniques With Adaptive Demodulation for Improved Perfusion Ultrasound Imaging Without Contrast

Noncontrast perfusion ultrasound imaging remains challenging due to spectral broadening of the tissue clutter signal caused by patient and sonographer hand motion. To address this problem, we previously introduced an adaptive demodulation scheme to suppress the bandwidth of tissue prior to high-pass filtering. Our initial implementation used single plane wave power Doppler imaging and a conventional tissue filter. Recent advancements in beamforming and tissue filtering have been proposed for improved slow flow imaging, including coherent flow power Doppler (CFPD) imaging and singular value decomposition (SVD) filtering. Here, we aim to evaluate adaptive demodulation in conjunction with improvements in beamforming and filtering using simulations, single-vessel phantoms, and an in vivo liver tumor embolization study. We show that simulated blood-to-background contrast-to-noise ratios are highest when using adaptive demodulation with CFPD and a 100-ms ensemble, which resulted in a 13.6-dB average increase in contrast-to-noise ratio compared to basic IIR filtering alone. We also show that combining adaptive demodulation with SVD and with CFPD + SVD results in 9.3- and 19-dB increases in contrast-to-noise ratios compared to IIR filtering alone at 700- and 500-ms ensembles for phantom data with 1- and 5-mm/s average flows, respectively. In general, combining techniques resulted in higher signal-to-noise, contrast-to-noise, and generalized contrast-to-noise ratios in both simulations and phantoms. Finally, adaptive demodulation with SVD resulted in the largest qualitative and quantitative changes in tumor-to-background contrast postembolization.

Short-lag Spatial Coherence Imaging in 1.5-D and 1.75-D Arrays: Elevation Performance and Array Design Considerations

Short-lag spatial coherence (SLSC) imaging has demonstrated improved performance over conventional B-Mode ultrasound imaging. Previous work has evaluated the performance of SLSC using 2-D matrix arrays in simulation and in vivo studies across various levels of subaperture beamforming, demonstrating improved contrast-to-noise ratio (CNR) and speckle signal-to-noise ratio (SNR) over 1-D arrays. This work explores the application of SLSC imaging in 1.5-D and 1.75-D arrays to quantify the impacts of elevation element count, mirroring, and Fresnel element spacing on SLSC image quality. Through simulation and in vivo studies, increased elevation element count was shown to improve CNR and speckle SNR relative to 1-D SLSC and B-Mode images. Elevation mirroring (1.5-D) was shown to force the inclusion of long lags into the SLSC calculation, introducing additional decorrelation and reducing image quality relative to 1.75-D arrays with individually-connected elements. These results demonstrate the effectiveness of SLSC imaging in 1.5-D and 1.75-D arrays.

Robust Short-Lag Spatial Coherence Imaging of Breast Ultrasound Data: Initial Clinical Results

Ultrasound is frequently used in conjunction with mammography in order to detect breast cancer as early as possible. However, due largely to the heterogeneity of breast tissue, ultrasound images are plagued with clutter that obstructs important diagnostic features. Short-lag spatial coherence (SLSC) imaging has proven to be effective at clutter reduction in noisy ultrasound images. M -Weighted SLSC and Robust-SLSC (R-SLSC) imaging were recently introduced to further improve image quality at higher lag values, while R-SLSC imaging has the added benefit of enabling the adjustment of tissue texture to produce a tissue signal-to-noise ratio (SNR) that is quantitatively similar to B-mode speckle SNR. This paper investigates the initial application of SLSC, M -Weighted SLSC, and R-SLSC imaging to nine targets in the female breast [two simple cysts, one complicated cyst, two fibroadenomas, one hematoma, one complex cystic and solid mass, one invasive ductal carcinoma (IDC), and one ductal carcinoma in situ (DCIS)]. As expected, R-SLSC beamforming improves cyst and hematoma contrast by up to 6.35 and 1.55 dB, respectively, when compared to the original B-mode image, and similar improvements are achieved with SLSC and M -Weighted SLSC imaging. However, an interesting finding from this initial investigation is that the solid masses (i.e., fibroadenoma, complex cystic and solid mass, IDC, and DCIS), which appear as hypoechoic in the B-mode image, have similarly high coherence to that of surrounding tissue in coherence-based images. This work holds promise for using SLSC, M -Weighted SLSC, and/or R-SLSC imaging to distinguish between fluid-filled and solid hypoechoic breast masses.

Improved Visualization in Difficult-to-Image Stress Echocardiography Patients Using Real-Time Harmonic Spatial Coherence Imaging

Stress echocardiography is used to detect myocardial ischemia by evaluating cardiovascular function both at rest and at elevated heart rates. Stress echocardiography requires excellent visualization of the left ventricle (LV) throughout the cardiac cycle. However, LV endocardial border visualization is often negatively impacted by high levels of clutter associated with patient obesity, which has risen dramatically worldwide in recent decades. Short-lag spatial coherence (SLSC) imaging has demonstrated reduced clutter in several applications. In this work, a computationally efficient formulation of SLSC was implemented into an object-oriented graphics processing unit-based software beamformer, enabling real-time (>30 frames per second) SLSC echocardiography on a research ultrasound scanner. The system was then used to image 15 difficult-to-image stress echocardiography patients in a comparison study of tissue harmonic imaging (THI) and harmonic spatial coherence imaging (HSCI). Video clips of four standard stress echocardiography views acquired with either THI or HSCI were provided in random shuffled order to three experienced readers. Each reader rated the visibility of 17 LV segments as "invisible," "suboptimally visualized," or "well visualized," with the first two categories indicating a need for contrast agent. In a symmetry test unadjusted for patientwise clustering, HSCI demonstrated a clear superiority over THI ( ). When measured on a per-patient basis, the median total score significantly favored HSCI with . When collapsing the ratings to a two-level scale ("needs contrast" versus "well visualized"), HSCI once again showed an overall superiority over THI, with by McNemar test adjusted for clustering.

High-Resolution Fast Ultrasound Imaging With Adaptive-Lag Filtered Delay-Multiply-and-Sum Beamforming and Multiline Acquisition

Multiline acquisition (MLA) is a well-established method for a high-frame-rate cardiac ultrasound imaging, which is commonly used in conjunction with delay-and-sum (DAS) beamforming. The block-like artifacts that occur secondary to the use of MLA can be reduced using interpolation of the data acquired from adjacent transmitted beams-a method called synthetic transmit beamforming (STB). A recently proposed filtered delay-multiply-and-sum (F-DMAS) is a novel beamforming method, based on modified autocorrelation of the aperture data, which provides superior contrast resolution compared to the DAS beamforming. In this study, we demonstrate that a combination of the F-DMAS with the STB compensated MLA results in superior contrast as compared to both DAS beamformed STB and DAS beamformed single-line acquisition. Moreover, we propose a novel formulation for adaptive-lag F-DMAS that outperforms both DAS and F-DMAS in terms of contrast and lateral resolutions. The results are demonstrated in tissue-mimicking phantom and in human cardiac data.

Optimization of the Trade-Off Between Speckle Reduction and Axial Resolution in Frequency Compounding

We measured the reduction of speckle by frequency compounding using Gaussian pulses, which have the least time-bandwidth product. The experimental results obtained from a tissue mimicking phantom agree quantitatively with numerical simulations of randomly distributed point scatterers. For a fixed axial resolution, the amount of speckle reduction is found to approach a maximum as the number of bands increases while the total spectral range that they cover is kept constant. An analytical solution of the maximal speckle reduction is derived and shows that the maximum improves approximately as the inverse square root of the Gaussian pulse bandwidth. Since the axial resolution is proportional to the inverse of the pulse bandwidth, an optimized trade-off between speckle reduction and axial resolution is obtained. Considerations for the applications of the optimized trade-off are discussed.

A Locally Adaptive Phase Aberration Correction (LAPAC) Method for Synthetic Aperture Sequences

Phase aberration is a phenomenon caused by heterogeneity of the speed of sound in tissue, in which the actual speed of sound of the tissue is different than the assumed speed of sound used for beamforming. It reduces the quality and resolution of ultrasonic images and impairs clinical diagnostic capabilities. Although phase aberration correction (PAC) methods can reduce these detrimental effects, most practical implementations of PAC methods are based on the near field phase screen model, which have limited ability to represent the true aberration induced by inhomogeneous tissue. Accordingly, we propose a locally adaptive phase aberration correction (LAPAC) method that is applied through the use of synthetic aperture. The method is tested using full-wave simulations of models of human abdominal wall, experiments with tissue aberrators, and in vivo carotid images. LAPAC is compared with conventional phase aberration correction (cPAC) where aberration profiles are computed at a preselected depth and applied to the beamformer's time delays. For all experiments, LAPAC shows an average of 1 to 2 dB higher contrast than cPAC, and enhancements of 3 to 7 dB with respect to the uncorrected cases. We conclude that LAPAC may be a viable option to enhance ultrasound image quality images even in the presence of clinically relevant aberrating conditions.

Sparse Convolutional Beamforming for Ultrasound Imaging

The standard technique used by commercial medical ultrasound systems to form B-mode images is delay and sum (DAS) beamforming. However, DAS often results in limited image resolution and contrast that are governed by the center frequency and the aperture size of the ultrasound transducer. A large number of elements lead to improved resolution but at the same time increase the data size and the system cost due to the receive electronics required for each element. Therefore, reducing the number of receiving channels while producing high-quality images is of great importance. In this paper, we introduce a nonlinear beamformer called COnvolutional Beamforming Algorithm (COBA), which achieves significant improvement of lateral resolution and contrast. In addition, it can be implemented efficiently using the fast Fourier transform. Based on the COBA concept, we next present two sparse beamformers with closed-form expressions for the sensor locations, which result in the same beam pattern as DAS and COBA while using far fewer array elements. Optimization of the number of elements shows that they require a minimal number of elements that are on the order of the square root of the number used by DAS. The performance of the proposed methods is tested and validated using simulated data, phantom scans, and in vivo cardiac data. The results demonstrate that COBA outperforms DAS in terms of resolution and contrast and that the suggested beamformers offer a sizable element reduction while generating images with an equivalent or improved quality in comparison with DAS.

Additive noise models for photoacoustic spatial coherence theory

Directly displaying the spatial coherence of photoacoustic signals (i.e., coherence-based photoacoustic imaging) remarkably improves image contrast, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and imaging depth when compared to conventional amplitude-based reconstruction techniques (e.g., backprojection, delay-and-sum beamforming, and Fourier-based reconstruction). We recently developed photoacoustic-specific theory to describe the spatial coherence process as a function of the element spacing on a receive acoustic aperture to enable photoacoustic image optimization without requiring experiments. However, this theory lacked noise models, which contributed to significant departures in coherence measurements when compared to experimental data, particularly at higher values of element separation. In this paper, we develop and implement two models based on experimental observations of noise in photoacoustic spatial coherence measurements to improve our existing spatial coherence theory. These models were derived to describe the effects of incident fluence variations, low-energy light sources (e.g., pulsed laser diodes and light-emitting diodes), averaging multiple signals from low-energy light sources, and imaging with light sources that are > 5mm from photoacoustic targets. Results qualitatively match experimental coherence functions and provide similar contrast, SNR, and CNR to experimental SLSC images. In particular, the added noise affects image quality metrics by introducing large variations in target contrast and significantly reducing target CNR and SNR when compared to minimal-noise cases. These results provide insight into additional requirements for optimization of coherence-based photoacoustic image quality.

An adaptive beamforming method for ultrasound imaging based on the mean-to-standard-deviation factor

The beamforming performance has a large impact on image quality in ultrasound imaging. Previously, several adaptive weighting factors including coherence factor (CF) and generalized coherence factor (GCF) have been proposed to improved image resolution and contrast. In this paper, we propose a new adaptive weighting factor for ultrasound imaging, which is called signal mean-to-standard-deviation factor (SMSF). SMSF is defined as the mean-to-standard-deviation of the aperture data and is used to weight the output of delay-and-sum (DAS) beamformer before image formation. Moreover, we develop a robust SMSF (RSMSF) by extending the SMSF to the spatial frequency domain using an altered spectrum of the aperture data. In addition, a square neighborhood average is applied on the RSMSF to offer a more smoothed square neighborhood RSMSF (SN-RSMSF) value. We compared our methods with DAS, CF, and GCF using simulated and experimental synthetic aperture data sets. The quantitative results show that SMSF results in an 82% lower full width at half-maximum (FWHM) but a 12% lower contrast ratio (CR) compared with CF. Moreover, the SN-RSMSF leads to 15% and 10% improvement, on average, in FWHM and CR compared with GCF while maintaining the speckle quality. This demonstrates that the proposed methods can effectively improve the image resolution and contrast.

Side lobe free medical ultrasonic imaging with application to assessing side lobe suppression filter

When focusing using an ultrasonic transducer array, a main lobe is formed in the focal region of an ultrasound field, but side lobes also arise around the focal region due to the leakage. Since the side lobes cannot be completely eliminated in the focusing process, they are responsible for subsequent ultrasound image quality degradation. To improve ultrasound image quality, a signal processing strategy to reduce side lobes is definitely in demand. To this end, quantitative determination of main and side lobes is necessary. We propose a theoretically and actually error-free method of exactly discriminating and separately computing the main lobe and side lobe parts in ultrasound image by computer simulation. We refer to images constructed using the main and side lobe signals as the main and side lobe images, respectively. Since the main and side lobe images exactly represent their main and side lobe components, respectively, they can be used to evaluate ultrasound image quality. Defining the average brightness of the main and side lobe images, the conventional to side lobe image ratio, and the main to side lobe image ratio as image quality metrics, we can evaluate image characteristics in speckle images. The proposed method is also applied in assessing the performance of side lobe suppression filtering. We show that the proposed method may greatly aid in the evaluation of medical ultrasonic images using computer simulations, albeit lacking the use of actual experimental data.