Short-lag Spatial Coherence Imaging Research Articles

Spatial Coherence Approaches to Distinguish Suspicious Mass Contents in Fundamental and Harmonic Breast Ultrasound Images.

When compared to fundamental B-mode imaging, coherence-based beamforming, and harmonic imaging are independently known to reduce acoustic clutter, distinguish solid from fluid content in indeterminate breast masses, and thereby reduce unnecessary biopsies during a breast cancer diagnosis. However, a systematic investigation of independent and combined coherence beamforming and harmonic imaging approaches is necessary for the clinical deployment of the most optimal approach. Therefore, we compare the performance of fundamental and harmonic images created with short-lag spatial coherence (SLSC), M-weighted SLSC (M-SLSC), SLSC combined with robust principal component analysis with no M-weighting (r-SLSC), and r-SLSC with M-weighting (R-SLSC), relative to traditional fundamental and harmonic B-mode images, when distinguishing solid from fluid breast masses. Raw channel data acquired from 40 total breast masses (28 solid, 7 fluid, 5 mixed) were beamformed and analyzed. The contrast of fluid masses was better with fundamental rather than harmonic coherence imaging, due to the lower spatial coherence within the fluid masses in the fundamental coherence images. Relative to SLSC imaging, M-SLSC, r-SLSC, and R-SLSC imaging provided similar contrast across multiple masses (with the exception of clinically challenging complicated cysts) and minimized the range of generalized contrast-to-noise ratios (gCNRs) of fluid masses, yet required additional computational resources. Among the eight coherence imaging modes compared, fundamental SLSC imaging best identified fluid versus solid breast mass contents, outperforming fundamental and harmonic B-mode imaging. With fundamental SLSC images, the specificity and sensitivity to identify fluid masses using the reader-independent metrics of contrast difference, mean lag one coherence (LOC), and gCNR were 0.86 and 1, 1 and 0.89, and 1 and 1, respectively. Results demonstrate that fundamental SLSC imaging and gCNR (or LOC if no coherence image or background region of interest is introduced) have the greatest potential to impact clinical decisions and improve the diagnostic certainty of breast mass contents. These observations are additionally anticipated to extend to masses in other organs.

Optimization of Short-Lag Spatial Coherence Imaging Method

The computing performance optimization of the Short-Lag Spatial Coherence (SLSC) method applied to ultrasound data processing is presented. The method is based on the theory that signals from adjacent receivers are correlated, drawing on a simplified conclusion of the van Cittert-Zernike theorem. It has been proven that it can be successfully used in ultrasound data reconstruction with despeckling. Former works have shown that the SLSC method in its original form has two main drawbacks: time-consuming processing and low contrast in the area near the transceivers. In this study, we introduce a method that allows to overcome both of these drawbacks. The presented approach removes the dependency on distance (the “lag” parameter value) between signals used to calculate correlations. The approach has been tested by comparing results obtained with the original SLSC algorithm on data acquired from tissue phantoms. The modified method proposed here leads to constant complexity, thus execution time is independent of the lag parameter value, instead of the linear complexity. The presented approach increases computation speed over 10 times in comparison to the base SLSC algorithm for a typical lag parameter value. The approach also improves the output image quality in shallow areas and does not decrease quality in deeper areas.

Spatial-coherence-based beamforming for image quality enhancement in high frame-rate ultrasound imaging

Several high frame-rate ultrasound imaging techniques have been recently proposed which allow to increase image acquisition rates by transmitting multiple focused beams simultaneously or defocused waves, and reconstructing multiple scan lines in parallel. These methods, which include for example multi-line transmission, plane/diverging wave imaging, and parallel beamforming, have proved to be successful in increasing the frame-rate, but on the other hand they have also showed some limitations in terms of the achievable image quality, partly degrading image contrast and resolution. Different solutions have been proposed to address this problem so far, such as the use of advanced receive beamforming algorithms able to improve the beam shape and the quality of the obtained image. Among these, beamformers based on backscattered signals spatial coherence, as e.g. Filtered Delay Multiply and Sum beamforming, Coherence-Factor-based methods, and Short Lag Spatial Coherence Imaging, have gained increasing attention for their ability to enhance image contrast and suppress clutter. In this presentation, an overview of some recent results obtained by jointly exploiting high frame-rate ultrasound imaging and coherence-based beamforming methods will be presented, showing through experimental tests the performance improvement achievable with these techniques.

Spatial Coherence Beamforming With Multi-Line Transmission to Enhance the Contrast of Coherent Structures in Ultrasound Images Degraded by Acoustic Clutter.

This work demonstrates that the combination of multi-line transmission (MLT) and short-lag spatial coherence (SLSC) imaging improves the contrast of highly coherent structures within soft tissues when compared to both traditional SLSC imaging and conventional delay and sum (DAS) beamforming. Experimental tests with small (i.e., [Formula: see text]-3 mm) targets embedded in homogeneous and heterogeneous backgrounds were conducted. DAS or SLSC images were reconstructed when implementing MLT with varying numbers of simultaneously transmitted beams. In images degraded by acoustic clutter, MLT SLSC achieved up to 34.1 dB better target contrast and up to 16 times higher frame rates when compared to the more conventional single-line transmission SLSC images, with lateral resolution improvements as large as 38.2%. MLT SLSC thus represents a promising technique for clinical applications in which ultrasound visualization of highly coherent targets is required (e.g., breast microcalcifications, kidney stones, and percutaneous biopsy needle tracking) and would otherwise be challenging due to the strong presence of acoustic clutter.

Reverberation Noise Suppression in Ultrasound Channel Signals Using a 3D Fully Convolutional Neural Network.

Diffuse reverberation is ultrasound image noise caused by multiple reflections of the transmitted pulse before returning to the transducer, which degrades image quality and impedes the estimation of displacement or flow in techniques such as elastography and Doppler imaging. Diffuse reverberation appears as spatially incoherent noise in the channel signals, where it also degrades the performance of adaptive beamforming methods, sound speed estimation, and methods that require measurements from channel signals. In this paper, we propose a custom 3D fully convolutional neural network (3DCNN) to reduce diffuse reverberation noise in the channel signals. The 3DCNN was trained with channel signals from simulations of random targets that include models of reverberation and thermal noise. It was then evaluated both on phantom and in-vivo experimental data. The 3DCNN showed improvements in image quality metrics such as generalized contrast to noise ratio (GCNR), lag one coherence (LOC) contrast-to-noise ratio (CNR) and contrast for anechoic regions in both phantom and in-vivo experiments. Visually, the contrast of anechoic regions was greatly improved. The CNR was improved in some cases, however the 3DCNN appears to strongly remove uncorrelated and low amplitude signal. In images of in-vivo carotid artery and thyroid, the 3DCNN was compared to short-lag spatial coherence (SLSC) imaging and spatial prediction filtering (FXPF) and demonstrated improved contrast, GCNR, and LOC, while FXPF only improved contrast and SLSC only improved CNR.

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., ) with mean ± standard deviation of signal-to-noise ratios of (compared with with conventional DAS beamforming). When energies were lower than the safety limit for skin (i.e., 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.

Photoacoustic Spatial Coherence Theory and Applications to Coherence-Based Image Contrast and Resolution.

The photoacoustic effect relies on optical transmission, which causes thermal expansion and generates acoustic signals. Coherence-based photoacoustic signal processing is often preferred over more traditional signal processing methods due to improved signal-to-noise ratios, imaging depth, and resolution in applications such as cell tracking, blood flow estimation, and imaging. However, these applications lack a theoretical spatial coherence model to support their implementation. In this article, the photoacoustic spatial coherence theory is derived to generate theoretical spatial coherence functions. These theoretical spatial coherence functions are compared with k-Wave simulated data and experimental data from point and circular targets (0.1-12 mm in diameter) with generally good agreement, particularly in the shorter spatial lag region. The derived theory was used to hypothesize and test previously unexplored principles for optimizing photoacoustic short-lag spatial coherence (SLSC) images, including the influence of the incident light profile on photoacoustic spatial coherence functions and associated SLSC image contrast and resolution. Results also confirm previous trends from experimental observations, including changes in SLSC image resolution and contrast as a function of the first M lags summed to create SLSC images. For example, small targets (e.g., <1-4 mm in diameter) can be imaged with larger M values to boost target contrast and resolution, and contrast can be further improved by reducing the illuminating beam to a size that is smaller than the target size. Overall, the presented theory provides a promising foundation to support a variety of coherence-based photoacoustic signal processing methods, and the associated theory-based simulation methods are more straightforward than the existing k-Wave simulation methods for SLSC images.

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.

Short-lag spatial coherence imaging with multi-line transmission to improve needle visibility in ultrasound images

Ultrasound Short Lag Spatial Coherence (SLSC) imaging exploits the spatial coherence (SC) of backscattered echoes to suppress acoustic clutter and to significantly improve image contrast, particularly in difficult-to-image patients. Multi-line transmission (MLT) imaging simultaneously transmits multiple beams to increase frame rates. We hypothesize that the combination of SLSC and MLT has the potential to enhance detectability of coherent structures within a tissue background. Sector images of a 14G biopsy needle inserted within ex vivo bovine meat were acquired after implementing single-line transmission (SLT) and MLT with 4, 6, 8 and 16 simultaneous beams. The SLSC algorithm was applied to the acquired data. Results show that MLT SLSC images have a visibly darker background than SLT SLSC images, which is caused by the rapid decorrelation of the SC at short lags with MLT. This decorrelation is caused by inter-beam crosstalk interferences and can be leveraged to enhance the coherence of highly reflective targets within a tissue background, causing an increase in needle contrast from about 25 dB with SLT to ∼44 dB with 16-MLT. These results support our hypothesis that the decorrelation caused by crosstalk improves visualization of highly coherent targets within tissue, with promising applications to biopsy needle localization.

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.

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.

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.

Feasibility of non-linear beamforming ultrasound methods to characterize and size kidney stones.

PurposeUltrasound methods for kidney stone imaging suffer from poor sensitivity and size overestimation. The study objective was to demonstrate feasibility of non-linear ultrasound beamforming methods for stone imaging, including plane wave synthetic focusing (PWSF), short-lag spatial coherence (SLSC) imaging, mid-lag spatial coherence (MLSC) imaging with incoherent compounding, and aperture domain model image reconstruction (ADMIRE).Materials and methodsThe ultrasound techniques were evaluated in an in vitro kidney stone model and in a pilot study of 5 human stone formers (n = 6 stones). Stone contrast, contrast-to-noise ratio (CNR), sizing, posterior shadow contrast, and shadow width sizing were compared among the different techniques and to B-mode. CT imaging within 60 days was considered the gold standard stone size. Paired t-tests using Bonferroni correction were performed to evaluate comparing each technique with B-mode.ResultsMean CT measured stone size was 6.0mm (range 2.9–12.2mm) with mean skin-to-stone distance 10.2cm (range 5.4–16.3cm). Compared to B-mode, stone contrast was best with ADMIRE (mean +12.2dB), while SLSC and MLSC showed statistically improved CNR. Sizing was best with ADMIRE (mean +1.3mm error), however this was not significantly improved over B-mode (+2.4mm). PWSF performed similarly to B-mode for stone contrast, CNR, SNR, and stone sizing. In the in vitro model, the shadow contrast was highest with ADMIRE (mean 10.5 dB vs 3.1 dB with B-mode). Shadow sizing was best with SLSC (mean error +0.9mm ± 2.9), however the difference compared to B-mode was not significant.ConclusionsThe detection and sizing of stones are feasible with advanced beamforming methods with ultrasound. ADMIRE, SLSC, and MLSC hold promise for improving stone detection, shadow contrast, and sizing.

MP63-01 FEASIBILITY OF NEXT GENERATION NON-LINEAR BEAMFORMING ULTRASOUND METHODS TO CHARACTERIZE AND SIZE KIDNEY STONES

You have accessJournal of UrologyImaging/Radiology: Uroradiology IV1 Apr 2018MP63-01 FEASIBILITY OF NEXT GENERATION NON-LINEAR BEAMFORMING ULTRASOUND METHODS TO CHARACTERIZE AND SIZE KIDNEY STONES Ryan Hsi, Siegfried Schlunk, Jaime Tierney, Rebecca Jones, Mark George, Pranav Karve, Ravindra Duddu, and Brett Byram Ryan HsiRyan Hsi More articles by this author , Siegfried SchlunkSiegfried Schlunk More articles by this author , Jaime TierneyJaime Tierney More articles by this author , Rebecca JonesRebecca Jones More articles by this author , Mark GeorgeMark George More articles by this author , Pranav KarvePranav Karve More articles by this author , Ravindra DudduRavindra Duddu More articles by this author , and Brett ByramBrett Byram More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2018.02.2024AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Advanced ultrasound beamforming methods for imaging kidney stones may help address the sensitivity and size overestimation problems with standard B-mode ultrasound. The study objective was to demonstrate feasibility of advanced ultrasound beamforming methods including plane wave synthetic focusing (PWSF), short-lag spatial coherence (SLSC) imaging, mid-lag spatial coherence (MLSC) imaging with incoherent compounding, and aperture domain model image reconstruction (ADMIRE). METHODS The ultrasound techniques were evaluated using a research-based ultrasound system applied to an in vitro kidney stone model (n=12, 4 and 8cm depths) and in a pilot study of human stone formers (n=5). Stone diameter sizing, shadow contrast, and stone contrast were compared among the different techniques and to B-mode. CT measurements were used to determine true stone size in the pilot study. Analysis of variance was used to analyze the differences among group means, and t-test when comparing to B-mode, with p<0.05 considered significant. RESULTS All stones were detectable with each method. In the in vitro study, MLSC performed best compared to B-mode for mean stone contrast (31.7 dB vs 14.7 dB, p<0.0025). On average, B-mode sizing error ± SD was >1mm (1.2±1.1 mm), while those for PWSF, ADMIRE, and MLSC were <1mm (-0.3±2.9mm, 0.6±0.8, 0.8±0.8, respectively). The mean posterior stone shadow contrast was highest with ADMIRE overall (ptrend=0.008), and when comparing between ADMIRE and B-mode (8.0 dB vs 2.1 dB, respectively; p=0.0131). In the pilot clinical study (Figure), mean stone contrast was best with ADMIRE and MLSC than with B mode (28.5 dB and 27.8 dB vs 18.1dB, respectively; ptrend=0.002). Mean sizing error was best with ADMIRE (+1.2mm), however there was no statistically significant difference when compared with B mode (+2.7mm). CONCLUSIONS The detection and sizing of stones are feasible with advanced beamforming methods with ultrasound. ADMIRE and MLSC hold promise for improving stone contrast, shadow contrast, and reducing sizing error. Future work will include imaging a broader population of human stone formers. © 2018FiguresReferencesRelatedDetails Volume 199Issue 4SApril 2018Page: e840-e841 Advertisement Copyright & Permissions© 2018MetricsAuthor Information Ryan Hsi More articles by this author Siegfried Schlunk More articles by this author Jaime Tierney More articles by this author Rebecca Jones More articles by this author Mark George More articles by this author Pranav Karve More articles by this author Ravindra Duddu More articles by this author Brett Byram More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

Robust Short-Lag Spatial Coherence Imaging.

Short-lag spatial coherence (SLSC) imaging displays the spatial coherence between backscattered ultrasound echoes instead of their signal amplitudes and is more robust to noise and clutter artifacts when compared with traditional delay-and-sum (DAS) B-mode imaging. However, SLSC imaging does not consider the content of images formed with different lags, and thus does not exploit the differences in tissue texture at each short-lag value. Our proposed method improves SLSC imaging by weighting the addition of lag values (i.e., M-weighting) and by applying robust principal component analysis (RPCA) to search for a low-dimensional subspace for projecting coherence images created with different lag values. The RPCA-based projections are considered to be denoised versions of the originals that are then weighted and added across lags to yield a final robust SLSC (R-SLSC) image. Our approach was tested on simulation, phantom, and in vivo liver data. Relative to DAS B-mode images, the mean contrast, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) improvements with R-SLSC images are 21.22 dB, 2.54, and 2.36, respectively, when averaged over simulated, phantom, and in vivo data and over all lags considered, which corresponds to mean improvements of 96.4%, 121.2%, and 120.5%, respectively. When compared with SLSC images, the corresponding mean improvements with R-SLSC images were 7.38 dB, 1.52, and 1.30, respectively (i.e., mean improvements of 14.5%, 50.5%, and 43.2%, respectively). Results show great promise for smoothing out the tissue texture of SLSC images and enhancing anechoic or hypoechoic target visibility at higher lag values, which could be useful in clinical tasks such as breast cyst visualization, liver vessel tracking, and obese patient imaging.

Clinical Utility of Fetal Short-Lag Spatial Coherence Imaging

In this study, we evaluate the clinical utility of fetal short-lag spatial coherence (SLSC) imaging. Previous work has documented significant improvements in image quality with fetal SLSC imaging as quantified by measurements of contrast and contrast-to-noise ratio (CNR). The objective of this study was to examine whether this improved technical efficacy is indicative of the clinical utility of SLSC imaging. Eighteen healthy volunteers in their first and second trimesters of pregnancy were scanned using a modified Siemens SC2000 clinical scanner. Raw channel data were acquired for routinely examined fetal organs and used to generate fully matched raw and post-processed harmonic B-mode and SLSC image sequences, which were subsequently optimized for dynamic range and other imaging parameters by a blinded sonographer. Optimized videos were reviewed in matched B-mode and SLSC pairs by three blinded clinicians who scored each video based on overall quality, target conspicuity and border definition. SLSC imaging was highly favored over conventional imaging with SLSC scoring equal to (28.2 ± 10.5%) or higher than (63.9 ± 12.9%) B-mode for video pairs across all examined structures and processing conditions. Multivariate modeling revealed that SLSC imaging is a significant predictor of improved image quality with p ≤ 0.002. Expert-user scores for image quality support the application of SLSC in fetal ultrasound imaging.

Short-lag spatial coherence combined with eigenspace-based minimum variance beamformer for synthetic aperture ultrasound imaging

Recently, short-lag spatial coherence (SLSC) imaging has been widely studied to improve image contrast and contrast-to-noise ratio (CNR) in ultrasound imaging. Nevertheless, SLSC is unable to provide a good imaging resolution. Eigenspace-based minimum variance (ESBMV) beamformer was previously devised to promote imaging resolution, while enhancing imaging contrast. However, ESBMV will cause black-spot artifact problem under a high threshold of eigenvalues. Given their complementary properties, in this study, we propose an imaging method with synthetic aperture (SA) ultrasound imaging by combining SLSC weighting (SLSCw) and ESBMV, to improve imaging quality at all depth. Based on the spatial coherence of different sources, adaptive threshold of eigenvalues is designed for ESBMV. In the proposed method, receive aperture data are directly summed to get the receive aperture synthesized data, and then SLSC and ESBMV are applied in transmit aperture based on the receive synthesized data. After that, the estimated SLSC value is adopted as a weighting factor for ESBMV beamforming output. We demonstrate the performance of the proposed method based on simulated and experimental data. The results show that the proposed method can not only achieve satisfactory improvement in resolution and contrast but also remove the black-spot artifacts.

Short-lag Spatial Coherence Ultrasound Imaging with Adaptive Synthetic Transmit Aperture Focusing.

The short-lag spatial coherence (SLSC) imaging has been demonstrated to be advantageous over the traditional B-mode ultrasound imaging. With focused scanning beams, the SLSC imaging has an excellent performance in clutter reduction and lesion detection, especially in the low signal-to-noise ratio (SNR) scenarios. The synthetic aperture (SA) imaging is an appropriate mode for the SLSC imaging as the dynamic transmit focusing could keep a good focusing quality at any depth. However, the SLSC image may still suffer a bad resolution performance when a low lag value is used in the coherence summation to ensure the contrast enhancement. In this paper, an adaptive synthetic transmit (Tx) aperture focusing strategy is proposed for the SLSC imaging with the SA mode. Based on the achievements of adaptive beamforming, a minimum variance beamformer is applied in the Tx aperture to realize adaptive focusing. Spatial coherence is then measured in the receive aperture to form the SLSC image. Simulation and experimental studies were conducted to evaluate the proposed method. Experiments showed that the proposed method not only improved the poor resolution of the original SLSC image but also enhanced the speckle performance, which led to increased contrast-to-noise ratio and speckle SNR values.

Resolution and brightness characteristics of short-lag spatial coherence (SLSC) images.

We previously described a novel beamforming method that images the spatial correlation of an echo wave field with demonstrated applications to clutter reduction in high-noise environments. In this paper, several characteristics of the resolution and brightness of short-lag spatial coherence (SLSC) images formed by this method are compared with B-mode images formed by conventional delay-and-sum beamforming methods. Point target widths were measured to estimate resolution, the autocorrelation of image texture was measured to estimate texture size, and the contrast (i.e., brightness ratio) of clinically relevant targets was assessed. SLSC images demonstrate improved resolution and contrast with increasing values of channel noise and clutter, whereas B-mode resolution was degraded in the presence of high noise (i.e., > -12 dB channel noise-to-signal ratios) and high clutter magnitudes (i.e., > -21 dB relative to point target magnitude). Lateral resolution in SLSC images was improved with increasing lag value, whereas axial resolution was degraded with increasing correlation kernel length. The texture size of SLSC images was smaller than that of matched B-mode images. Results demonstrate that the resolution and contrast of coherence-based images depend on a range of parameters, but are generally superior to those of matched B-mode images under challenging imaging conditions.

Acoustic reciprocity of spatial coherence in ultrasound imaging.

A conventional ultrasound image is formed by transmitting a focused wave into tissue, time-shifting the backscattered echoes received on an array transducer, and summing the resulting signals. The van Cittert-Zernike theorem predicts a particular similarity, or coherence, of these focused signals across the receiving array. Many groups have used an estimate of the coherence to augment or replace the B-mode image in an effort to suppress noise and stationary clutter echo signals, but this measurement requires access to individual receive channel data. Most clinical systems have efficient pipelines for producing focused and summed RF data without any direct way to individually address the receive channels. We describe a method for performing coherence measurements that is more accessible for a wide range of coherence-based imaging. The reciprocity of the transmit and receive apertures in the context of coherence is derived and equivalence of the coherence function is validated experimentally using a research scanner. The proposed method is implemented on a commercial ultrasound system and in vivo short-lag spatial coherence imaging is demonstrated using only summed RF data. The components beyond the acquisition hardware and beamformer necessary to produce a real-time ultrasound coherence imaging system are discussed.