Multilevel and motion model-based ultrasonic speckle tracking algorithms

Advanced synthetic aperture technique to enhance image quality in ultrasound elastography: A novel strategy

Quasi-static elastography (QSE) is a well-established technique used in medical imaging, where ultrasound data is collected both, before and after applying a slight compression on a tissue. This data is then analyzed to create image frames that reveal the stiffness parameter of the underlying tissue medium. Previous studies have focused on assessing how the Conventional Focused Beam (CFB) transmit method impacts the ultrasound elastography image quality. Recent studies have also shown an interest in synthetic aperture techniques like the Diverging Beam Synthetic Aperture Technique (DBSAT), due to its potential to enhance ultrasound image quality. However, its application in elastography has received limited attention. This paper introduces a new strategy of averaging low-resolution elastogram frames (LREA), obtained from DBSAT transmit method to improve the quality of elastography images. The CFB technique involves scanning the tissue line by line. In contrast, DBSAT is a synthetic aperture method that generates multiple low-resolution elastogram frames before combining them together to create a single high-quality image. In this research paper all the experimental studies were conducted on an agar-gelatin phantom, demonstrating the effectiveness of estimating elastograms from the low-resolution frame data of DBSAT transmit scheme and then summing them together to produce an elastogram with enhanced image quality. The results show a maximum improvement of 8 dB in the image quality metric of signal-to-noise ratio (SNR) as well as a 7 dB improvement in contrast-to-noise ratio (CNR) when comparing elastography images obtained by the proposed LREA method and the elastography images obtained by regular processing of the RF data acquired using the different methods of CFB and DBSAT.

Teacher-student guided knowledge distillation for unsupervised convolutional neural network-based speckle tracking in ultrasound strain elastography

Accurate and efficient motion estimation is a crucial component of real-time ultrasound elastography (USE). However, obtaining radiofrequency ultrasound (RF) data in clinical practice can be challenging. In contrast, although B-mode (BM) data is readily available, elastographic data derived from BM data results in sub-optimal elastographic images. Furthermore, existing conventional ultrasound devices (e.g., portable devices) cannot provide elastography modes, which has become a significant obstacle to the widespread use of traditional ultrasound devices. To address the challenges above, we developed a teacher-student guided knowledge distillation for an unsupervised convolutional neural network (TSGUPWC-Net) to improve the accuracy of BM motion estimation by employing a well-established convolutional neural network (CNN) named modified pyramid warping and cost volume network (MPWC-Net). A pre-trained teacher model based on RF is utilized to guide the training of a student model using BM data. Innovations outlined below include employing spatial attention transfer at intermediate layers to enhance the guidance effect of the model. The loss function consists of smoothness of the displacement field, knowledge distillation loss, and intermediate layer loss. We evaluated our method on simulated data, phantoms, and in vivo ultrasound data. The results indicate that our method has higher signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) values in axial strain estimation than the model trained on BM. The model is unsupervised and requires no ground truth labels during training, making it highly promising for motion estimation applications.

Dynamic Coronary Blood Flow Velocity and Wall Shear Stress Estimation Using Ultrasound in an Ex Vivo Porcine Heart

PURPOSE

Wall shear stress (WSS) is a critically important physical factor contributing to atherosclerosis. Mapping the spatial distribution of local, oscillatory WSS can identify important mechanisms underlying the progression of coronary artery disease.

METHODS

In this study, blood flow velocity and time-varying WSS were estimated in the left anterior descending (LAD) coronary artery of an ex vivo beating porcine heart using ultrasound with an 18 MHz linear array transducer aligned with the LAD in a forward-viewing orientation. A pulsatile heart loop with physiologically-accurate flow was created using a pulsatile pump. The coronary artery wall motion was compensated using a local block matching technique. Next, 2D and 3D velocity magnitude and WSS maps in the LAD coronary artery were estimated at different time points in the cardiac cycle using an ultrafast Doppler approach. The blood flow velocity estimated using the presented approach was compared with a commercially-available, calibrated single element blood flow velocity measurement system.

RESULTS

The resulting root mean square error (RMSE) of 2D velocity magnitude acquired from a high frequency, linear array transducer was less than 8% of the maximum velocity estimated by the commercial system.

CONCLUSION

When implemented in a forward-viewing intravascular ultrasound device, the presented approach will enable dynamic estimation of WSS, an indicator of plaque vulnerability in coronary arteries.

A GPU-Based, Real-Time Dealiasing Framework for High-Frame-Rate Vector Doppler Imaging

Vector Doppler is well regarded as a potential way of deriving flow vectors to intuitively visualize complex flow profiles, especially when it is implemented at high frame rates. However, this technique's performance is known to suffer from aliasing artifacts. There is a dire need to devise real-time dealiasing solutions for vector Doppler. In this article, we present a new methodological framework for achieving aliasing-resistant flow vector estimation at real-time throughput from precalculated Doppler frequencies. Our framework comprises a series of compute kernels that have synergized: 1) an extended least squares vector Doppler (ELS-VD) algorithm; 2) single-instruction, multiple-thread (SIMT) processing principles; and 3) implementation on a graphical processing unit (GPU). Results show that this new framework, when executed on an RTX-2080 GPU, can effectively generate aliasing-free flow vector maps using high-frame-rate imaging datasets acquired from multiple transmit-receive angle pairs in a carotid phantom imaging scenario. Over the entire cardiac cycle, the frame processing time for aliasing-resistant vector estimation was measured to be less than 16 ms, which corresponds to a minimum processing throughput of 62.5 frames/s. In a human femoral bifurcation imaging trial with fast flow (150 cm/s), our framework was found to be effective in resolving two-cycle aliasing artifacts at a minimum throughput of 53 frames/s. The framework's processing throughput was generally in the real-time range for practical combinations of ELS-VD algorithmic parameters. Overall, this work represents the first demonstration of real-time, GPU-based aliasing-resistant vector flow imaging using vector Doppler estimation principles.

Unsupervised Convolutional Neural Network for Motion Estimation in Ultrasound Elastography

High-quality motion estimation is essential for ultrasound elastography (USE). Traditional motion estimation algorithms based on speckle tracking such as normalized cross correlation (NCC) or regularization such as global ultrasound elastography (GLUE) are time-consuming. In order to reduce the computational cost and ensure the accuracy of motion estimation, many convolutional neural networks have been introduced into USE. Most of these networks such as radio-frequency modified pyramid, warping and cost volume network (RFMPWC-Net) are supervised and need many ground truths as labels in network training. However, the ground truths are laborious to collect for USE. In this study, we proposed a MaskFlownet-based unsupervised convolutional neural network (MF-UCNN) for fast and high-quality motion estimation in USE. The inputs to MF-UCNN are the concatenation of RF, envelope, and B-mode images before and after deformation, while the outputs are the axial and lateral displacement fields. The similarity between the predeformed image and the warped image (i.e., the postdeformed image compensated by the estimated displacement fields) and the smoothness of the estimated displacement fields were incorporated in the loss function. The network was compared with modified pyramid, warping and cost volume network (MPWC-Net)++, RFMPWC-Net, GLUE, and NCC. Results of simulations, breast phantom, and in vivo experiments show that MF-UCNN obtains higher signal-to-noise ratio (SNR) and higher contrast-to-noise ratio (CNR). MF-UCNN achieves high-quality motion estimation with significantly reduced computation time. It is unsupervised and does not need any ground truths as labels in the training, and, thus, has great potential for motion estimation in USE.

A Robust and Fast Method for 2-D Shear Wave Speed Calculation

We developed a new method, called the tangent plane method (TPM), for more efficiently and accurately estimating 2-D shear wave speed (SWS) from any direction of wave propagation. In this technique, we estimate SWS by solving the Eikonal equation because this approach is more robust to noise. To further enhance the performance, we computed the tangent plane of the arrival time surface. To evaluate the approach, we performed simulations and also conducted phantom studies. Simulation studies showed that TPM was more robust to noise than the conventional methods such as 2-D cross correlation (CC) and the distance method. The contrast/CNR for an inclusion (69 kPa; manufacturer provided stiffness) of a phantom is 0.54/4.17, 0.54/1.82, and 0.46/1.22. SWS results [mean and standard deviation (SD)] were 4.41 ± 0.49, 4.62 ± 0.85, and 3.66 ± 0.99 m/s, respectively, while the manufacturer's reported value (mean and range) is 4.81 ± 0.49 m/s. This shows that TPM has the higher CNR and lower SD than other methods. To increase the computation speed, an iterative version of TPM (ITPM) was also developed, which calculated the time-of-flight iteratively. ITPM reduced the computation time to 3.6%, i.e., from 748 to 27 s. In vivo case analysis demonstrated the feasibility of using the conventional ultrasound scanner for the proposed 2-D SWS algorithms.

Optimum Speckle Tracking Based on Ultrafast Ultrasound for Improving Blood Flow Velocimetry

Speckle tracking using optimum comparison frames (STO) is proposed to improve the blood flow velocity profile (BFVP) estimation based on ultrafast ultrasound with coherent plane-wave compounding. The optimum comparison frames are as far as possible from the reference frame image while possessing a speckle correlation above a given threshold. The correlation thresholds for different kernel sizes are determined via an experiment based on a vascular-mimicking phantom. In in vitro experiments with different peak velocities of the flow ranging from 0.38 to 1.18 m/s, the proposed STO method with three kernel sizes ( 0.46 × 0.46 , 0.31 × 0.69 , and 0.92 × 0.92 mm²) is used for the BFVP estimations. The normalized root mean square errors (NRMSEs) between the estimated and theoretical BFVPs are calculated and compared with the results based on the speckle tracking using adjacent-frame images. For the three kernel sizes, the mean relative decrements in the STO-based NRMSEs are 46.6%, 44.7%, and 52.9%, and the standard deviations are 36.8%, 37.6%, and 35.9%, respectively. The STO method is also validated by in vivo experiments using rabbit iliac arteries with contrast agents. With parabolic curves fitting to the mean velocity estimates, the average relative increments for the STO-based R² (coefficients of determination) are 7.22% and 6.25% for kernel sizes of 0.46 × 0.46 and 0.31 × 0.69 mm², respectively. In conclusion, the STO method improves the BFVP measurement accuracy, whereby accurate diagnosis information can be acquired for clinical applications.

Spatial-Semantic and Temporal Attention Mechanism-Based Online Multi-Object Tracking

Multi-object tracking (MOT) plays a crucial role in various platforms. Occlusion and insertion among targets, complex backgrounds and higher real-time requirements increase the difficulty of MOT problems. Most state-of-the-art MOT approaches adopt the tracking-by-detection strategy, which relies on compute-intensive sliding windows or anchoring schemes to detect matching targets or candidates in each frame. In this work, we introduce a more efficient and effective spatial-temporal attention scheme to track multiple objects in various scenarios. Using a semantic-feature-based spatial attention mechanism and a novel Motion Model, we address the insertion and location of candidates. Some online-learned target-specific convolutional neural networks (CNNs) were used to estimate target occlusion and classify by adapting the appearance model. A temporal attention mechanism was adopted to update the online module by balancing current and history frames. Extensive experiments were performed on Karlsruhe Institute of Technologyand Toyota Technological Institute (KITTI) benchmarks and an Armored Target Tracking Dataset (ATTD) built for ground-armored targets. Experimental results show that the proposed method achieved outstanding tracking performance and met the actual application requirements.

An Improved Region-Growing Motion Tracking Method Using More Prior Information for 3-D Ultrasound Elastography

Three-dimensional (3-D) ultrasound elastography can provide 3-D tissue stiffness information that may be used during clinical diagnoses. In the framework of strain elastography, motion tracking plays an important role. In this study, an improved 3-D region-growing motion tracking (RGMT) algorithm based on a concept of exterior boundary points was developed. In principle, the proposed method first determines displacement at some seed points by strictly checking the local correlation and continuity in the neighborhood of those seeds. Subsequent displacement estimation is then conducted from these initial seeds to obtain displacements associated with other locations. This RGMT algorithm is designed to use more known information-including displacements and correlation values of all known-displacement neighboring points-to estimate the displacement of an unknown-displacement point, whereas previous RGMT methods employed information from only one such point. The algorithm was tested on 3-D ultrasound volumetric data acquired from a simulation, a tissue-mimicking phantom, and five human subjects. Motion-compensated cross correlations (MCCCs), strain contrast, and displacement Laplacian values (representing smoothness of an estimated displacement field) were calculated and used to evaluate the merits of the proposed RGMT method. Compared with a previously published RGMT method, the results show that the proposed RGMT method can provide smaller displacement errors and smoother displacements and improve strain contrast while maintaining reasonably high MCCC values, indicating good motion tracking quality. The proposed method is also computationally more efficient. In summary, our preliminary results demonstrated that the proposed RGMT algorithm is capable of obtaining high-quality 3-D strain elastographic data using modified clinical equipment.

Estimation of absolute states of human skeletal muscle via standard B-mode ultrasound imaging and deep convolutional neural networks

The objective is to test automated in vivo estimation of active and passive skeletal muscle states using ultrasonic imaging. Current technology (electromyography, dynamometry, shear wave imaging) provides no general, non-invasive method for online estimation of skeletal muscle states. Ultrasound (US) allows non-invasive imaging of muscle, yet current computational approaches have never achieved simultaneous extraction or generalization of independently varying active and passive states. We use deep learning to investigate the generalizable content of two-dimensional (2D) US muscle images. US data synchronized with electromyography of the calf muscles, with measures of joint moment/angle, were recorded from 32 healthy participants (seven female; ages: 27.5, 19–65). We extracted a region of interest of medial gastrocnemius and soleus using our prior developed accurate segmentation algorithm. From the segmented images, a deep convolutional neural network was trained to predict three absolute, drift-free components of the neurobiomechanical state (activity, joint angle, joint moment) during experimentally designed, simultaneous independent variation of passive (joint angle) and active (electromyography) inputs. For all 32 held-out participants (16-fold cross-validation) the ankle joint angle, electromyography and joint moment were estimated to accuracy 55 ± 8%, 57 ± 11% and 46 ± 9%, respectively. With 2D US imaging, deep neural networks can encode, in generalizable form, the activity–length–tension state relationship of these muscles. Observation-only, low-power 2D US imaging can provide a new category of technology for non-invasive estimation of neural output, length and tension in skeletal muscle. This proof of principle has value for personalized muscle assessment in pain, injury, neurological conditions, neuropathies, myopathies and ageing.

Imaging modalities to diagnose carotid artery stenosis: progress and prospect

In the past few decades, imaging has been developed to a high level of sophistication. Improvements from one-dimension (1D) to 2D images, and from 2D images to 3D models, have revolutionized the field of imaging. This not only helps in diagnosing various critical and fatal diseases in the early stages but also contributes to making informed clinical decisions on the follow-up treatment profile. Carotid artery stenosis (CAS) may potentially cause debilitating stroke, and its accurate early detection is therefore important. In this paper, the technical development of various CAS diagnosis imaging modalities and its impact on the clinical efficacy is thoroughly reviewed. These imaging modalities include duplex ultrasound (DUS), computed tomography angiography (CTA) and magnetic resonance angiography (MRA). For each of the imaging modalities considered, imaging methodology (principle), critical imaging parameters, and the extent of imaging the vulnerable plaque are discussed. DUS is usually the initial recommended CAS diagnostic examination. However, for the therapeutic intervention, either MRA or CTA is recommended for confirmation, and for added information on intracranial cerebral circulation and aortic arch condition for procedural planning. Over the past few decades, the focus of CAS diagnosis has also shifted from pure stenosis quantification to plaque characterization. This has led to further advancement in the existing imaging tools and development of other potential imaging tools like Optical coherence tomography (OCT), photoacoustic tomography (PAT), and infrared (IR) thermography.

Motion Estimation in Echocardiography Using Sparse Representation and Dictionary Learning

This paper introduces a new method for cardiac motion estimation in 2-D ultrasound images. The motion estimation problem is formulated as an energy minimization, whose data fidelity term is built using the assumption that the images are corrupted by multiplicative Rayleigh noise. In addition to a classical spatial smoothness constraint, the proposed method exploits the sparse properties of the cardiac motion to regularize the solution via an appropriate dictionary learning step. The proposed method is evaluated on one data set with available ground-truth, including four sequences of highly realistic simulations. The approach is also validated on both healthy and pathological sequences of in vivo data. We evaluate the method in terms of motion estimation accuracy and strain errors and compare the performance with state-of-the-art algorithms. The results show that the proposed method gives competitive results for the considered data. Furthermore, the in vivo strain analysis demonstrates that meaningful clinical interpretation can be obtained from the estimated motion vectors.This paper introduces a new method for cardiac motion estimation in 2-D ultrasound images. The motion estimation problem is formulated as an energy minimization, whose data fidelity term is built using the assumption that the images are corrupted by multiplicative Rayleigh noise. In addition to a classical spatial smoothness constraint, the proposed method exploits the sparse properties of the cardiac motion to regularize the solution via an appropriate dictionary learning step. The proposed method is evaluated on one data set with available ground-truth, including four sequences of highly realistic simulations. The approach is also validated on both healthy and pathological sequences of in vivo data. We evaluate the method in terms of motion estimation accuracy and strain errors and compare the performance with state-of-the-art algorithms. The results show that the proposed method gives competitive results for the considered data. Furthermore, the in vivo strain analysis demonstrates that meaningful clinical interpretation can be obtained from the estimated motion vectors.

Ultrasound 2D strain measurement for arm lymphedema using deformable registration: A feasibility study

Purpose

Lymphedema, a swelling of the extremity, is a debilitating morbidity of cancer treatment. Current clinical evaluation of lymphedema is often based on medical history and physical examinations, which is subjective. In this paper, the authors report an objective, quantitative 2D strain imaging approach using a hybrid deformable registration to measure soft-tissue stiffness and assess the severity of lymphedema.

Methods

The authors have developed a new 2D strain imaging method using registration of pre- and post-compression ultrasound B-mode images, which combines the statistical intensity- and structure-based similarity measures using normalized mutual information (NMI) metric and normalized sum-of-squared-differences (NSSD), with an affine-based global and B-spline-based local transformation model. This 2D strain method was tested through a series of experiments using elastography phantom under various pressures. Clinical feasibility was tested with four participants: two patients with arm lymphedema following breast-cancer radiotherapy and two healthy volunteers.

Results

The phantom experiments have shown that the proposed registration-based strain method significantly increased the signal-to-noise and contrast-to-noise ratio under various pressures as compared with the commonly used cross-correlation-based elastography method. In the pilot study, the strain images were successfully generated for all participants. The averaged strain values of the lymphedema affected arms were much higher than those of the normal arms.

Conclusions

The authors have developed a deformable registration-based 2D strain method for the evaluation of arm lymphedema. The initial findings are encouraging and a large clinical study is warranted to further evaluate this 2D ultrasound strain imaging technology.

Ultrasound Vector Flow Imaging-Part I: Sequential Systems

This paper gives a review of the most important methods for blood velocity vector flow imaging (VFI) for conventional sequential data acquisition. This includes multibeam methods, speckle tracking, transverse oscillation, color flow mapping derived VFI, directional beamforming, and variants of these. The review covers both 2-D and 3-D velocity estimation and gives a historical perspective on the development along with a summary of various vector flow visualization algorithms. The current state of the art is explained along with an overview of clinical studies conducted and methods for presenting and using VFI. A number of examples of VFI images are presented, and the current limitations and potential solutions are discussed.

Deformable regions of interest with multiple points for tissue tracking in echocardiography

By tracking echocardiography images more accurately and stably, we can better assess myocardial functions. In this paper, we propose a new tracking method with deformable Regions of Interest (ROIs) aiming at rational pattern matching. For this purpose we defined multiple tracking points for an ROI and regarded these points as nodes in the Meshfree Method to interpolate displacement fields. To avoid unreasonable distortion of the ROI caused by noise and perturbation in echo images, we introduced a stabilization technique based on a nonlinear strain energy function. Examples showed that the combination of our new tracking method and stabilization technique provides competitive and stable tracking.

Optimization-Based Speckle Tracking Algorithm for Left Ventricle Strain Estimation: A Feasibility Study

Speckle tracking echocardiography (STE) is a widespread method for calculating myocardial strains and estimating left ventricle function. Since echocardiographic clips are corrupted by speckle decorrelation noise, resulting in irregular, nonphysiological tissue displacement fields, smoothing is performed on the displacement data, affecting the strain results. Thus, strain results may depend on the specific implementations of 2-D STE, as well as other systems' characteristics of the various vendors. A novel algorithm (called K-SAD) is introduced, which integrates the physiological constraint of smoothness of the displacement field into an optimization process. Simulated B-mode clips, modeling healthy and abnormal cases, were processed by K-SAD. Peak global and subendocardial longitudinal strains, as well as regional strains, were calculated. In addition, 410 healthy subjects were also processed. The results of K-SAD are compared with those of one of the leading commercial product. K-SAD provides global mid-wall strain values, as well as subendocardial and regional strain values, all in good agreement with the ground-truth-simulated phantom data. K-SAD peak global longitudinal systolic strain values for 410 healthy subjects are quite similar for the different regions: - 17.02 ± 4.02%, - 19.00 ± 3.45%, and - 19.72 ± 5.06% at the basal, mid, and apical regions, respectively. Improved performance under noisy conditions was demonstrated by comparing a subgroup of 40 subjects with the best image quality with the remaining 370 cohort: K-SAD provides statistically similar global and regional results for the two cohorts. Our study indicates that the sensitivity of strain values to speckle noise, caused by the post block-matching weighted smoothing, can be significantly reduced and accuracy enhanced by employing an integrated one-stage, physiologically constrained optimization process.

Influence of ultrasound speckle tracking strategies for motion and strain estimation

Speckle Tracking is one of the most prominent techniques used to estimate the regional movement of the heart based on ultrasound acquisitions. Many different approaches have been proposed, proving their suitability to obtain quantitative and qualitative information regarding myocardial deformation, motion and function assessment. New proposals to improve the basic algorithm usually focus on one of these three steps: (1) the similarity measure between images and the speckle model; (2) the transformation model, i.e. the type of motion considered between images; (3) the optimization strategies, such as the use of different optimization techniques in the transformation step or the inclusion of structural information. While many contributions have shown their good performance independently, it is not always clear how they perform when integrated in a whole pipeline. Every step will have a degree of influence over the following and hence over the final result. Thus, a Speckle Tracking pipeline must be analyzed as a whole when developing novel methods, since improvements in a particular step might be undermined by the choices taken in further steps. This work presents two main contributions: (1) We provide a complete analysis of the influence of the different steps in a Speckle Tracking pipeline over the motion and strain estimation accuracy. (2) The study proposes a methodology for the analysis of Speckle Tracking systems specifically designed to provide an easy and systematic way to include other strategies. We close the analysis with some conclusions and recommendations that can be used as an orientation of the degree of influence of the models for speckle, the transformation models, interpolation schemes and optimization strategies over the estimation of motion features. They can be further use to evaluate and design new strategy into a Speckle Tracking system.

Reduced common carotid artery longitudinal wall motion and intramural shear strain in individuals with elevated cardiovascular disease risk using speckle tracking

Longitudinal motion of the intima-media and adventitia layers of the common carotid artery (CCA) wall were assessed with ultrasound speckle tracking in seven individuals with spinal cord injury (SCI), who are considered at increased risk of cardiovascular disease, and in seven able-bodied participants. CCA longitudinal wall displacement and intramural shear strain were compared to traditional markers of arterial health, including CCA stiffness and intima-media thickness (IMT). For each cardiac cycle, longitudinal CCA wall motion was characterized by bidirectional movement patterns containing motion retrograde to blood flow during systole, followed by antegrade motion during diastole. Relative displacement of the intima-media versus the adventitia was used to calculate longitudinal intramural shear strain and provided insight to local arterial wall properties. The retrograde intramural shear strain was smaller in individuals with SCI by 60·2% (P<0·05) compared to able-bodied participants, showing smaller peak displacements in both the intima-media (P<0·05) and adventitia (P<0·05). In the antegrade direction, there were no group differences in either longitudinal displacements or shear strain. The group differences observed in the retrograde wall motion phase were greater than those observed for CCA stiffness or IMT and were found to be independent of both indices, indicating indices of the retrograde phase intramural shear strain may be a novel and sensitive marker of vascular health. Our findings demonstrate that assessment of longitudinal arterial wall shear strain may provide valuable insight into vascular structure and function and may hold potential for the early detection of cardiovascular disease.

Validation of color Doppler sonography for evaluating relative displacement between the flexor tendon and subsynovial connective tissue

OBJECTIVES

A common pathologic finding in carpal tunnel syndrome is fibrosis and thickening of the subsynovial connective tissue. This finding suggests an etiology of excessive shear forces, with relative longitudinal displacement between the flexor tendon and adjacent subsynovial connective tissue. The purpose of this study was to validate color Doppler sonography for measurement of tendon displacement over time.

METHODS

Eight unmatched fresh frozen cadaver arms were used to evaluate color Doppler sonography for measurement of tendon displacement. The middle flexor digitorum superficialis tendon was moved through a physiologic excursion of 20 mm at 3 different tendon velocities (50, 100, and 150 mm/s).

RESULTS

We found that color Doppler sonography provided accurate measurement of tendon displacement, with absolute errors of -0.05 mm (50 mm/s), -1.24 mm (100 mm/s), and -2.36 mm (150 mm/s) on average throughout the tendon excursion range. Evaluating relative displacement between the tendon and subsynovial connective tissue during finger flexion-extension movements also offered insight into the gliding mechanism of the subsynovial connective tissue. During flexion, we observed a curvilinear increase in relative displacement, with greater differential motion at the end range of displacement, likely due to the sequential stretch of the fibrils between successive layers of the subsynovial connective tissue. In extension, there was a linear return in relative displacement, suggesting a different unloading mechanism characterized by uniform relaxation of fibrils.

CONCLUSIONS

We demonstrated the validity of color Doppler displacement for use in the evaluation of relative motion. Color Doppler sonography is useful in our understanding of the behavior of the subsynovial connective tissue during tendon excursion, which may elucidate the role of finger motion in the etiology of shear injury.

3-D ultrasonic strain imaging based on a linear scanning system

This paper introduces a 3-D strain imaging method based on a freehand linear scanning mode. We designed a linear sliding track with a position sensor and a height-adjustable holder to constrain the movement of an ultrasound probe in a freehand manner. When moving the probe along the sliding track, the corresponding positional measures for the probe are transmitted via a wireless communication module based on Bluetooth in real time. In a single examination, the probe is scanned in two sweeps in which the height of the probe is adjusted by the holder to collect the pre- and postcompression radio-frequency echoes, respectively. To generate a 3-D strain image, a volume cubic in which the voxels denote relative strains for tissues is defined according to the range of the two sweeps. With respect to the post-compression frames, several slices in the volume are determined and the pre-compression frames are re-sampled to precisely correspond to the post-compression frames. Thereby, a strain estimation method based on minimizing a cost function using dynamic programming is used to obtain the 2-D strain image for each pair of frames from the re-sampled pre-compression sweep and the post-compression sweep, respectively. A software system is developed for volume reconstruction, visualization, and measurement of the 3-D strain images. The experimental results show that high-quality 3-D strain images of phantom and human tissues can be generated by the proposed method, indicating that the proposed system can be applied for real clinical applications (e.g., musculoskeletal assessments).

In vivo acoustic super-resolution and super-resolved velocity mapping using microbubbles

The structure of microvasculature cannot be resolved using standard clinical ultrasound (US) imaging frequencies due to the fundamental diffraction limit of US waves. In this work, we use a standard clinical US system to perform in vivo sub-diffraction imaging on a CD1, female mouse aged eight weeks by localizing isolated US signals from microbubbles flowing within the ear microvasculature, and compare our results to optical microscopy. Furthermore, we develop a new technique to map blood velocity at super-resolution by tracking individual bubbles through the vasculature. Resolution is improved from a measured lateral and axial resolution of 112 μm and 94 μ m respectively in original US data, to super-resolved images of microvasculature where vessel features as fine as 19 μm are clearly visualized. Velocity maps clearly distinguish opposing flow direction and separated speed distributions in adjacent vessels, thereby enabling further differentiation between vessels otherwise not spatially separated in the image. This technique overcomes the diffraction limit to provide a noninvasive means of imaging the microvasculature at super-resolution, to depths of many centimeters. In the future, this method could noninvasively image pathological or therapeutic changes in the microvasculature at centimeter depths in vivo.

Adaptive motion estimation of shear shock waves in soft solids and tissue with ultrasound

Shear shock waves in soft solids, such as in tissue, have different regions of complex motion that can change rapidly across a single wave profile, especially at the shock front. Conventional tracking algorithms are not well adapted to the task of simultaneously tracking the discontinuous shock front and smooth regions away from the shock. An adaptive algorithm based on the normalized cross-correlation and a correlation-weighted median filter is presented. The proposed adaptive algorithm combines two features: first, it adapts the window size to optimize the correlation value based on the deformation, and second, it rejects inaccurate estimates with a median-weighted filter. For simulated ultrasound data, where the displacements are known, it is shown that the estimated velocity error for the adaptive algorithm is less than 1/3 of the error for non-adaptive normalized cross-correlation. The addition of the weighted median filter to the adaptive algorithm significantly improves the shock tracking performance. The shock position and rise-time error is almost an order of magnitude better with the median-weighted filter. This algorithm is then used to track shock wave propagation with data acquired by a high-frame-rate ultrasound scanner in a tissue-mimicking agar and gelatin phantom. The shock front is not resolved with conventional algorithms but it is clearly visible with the proposed adaptive median-weighted algorithm.

A new technique for the estimation of cardiac motion in echocardiography based on transverse oscillations: a preliminary evaluation in silico and a feasibility demonstration in vivo

Quantification of regional myocardial motion and deformation from cardiac ultrasound is fostering considerable research efforts. Despite the tremendous improvements done in the field, all existing approaches still face a common limitation which is intrinsically connected with the formation of the ultrasound images. Specifically, the reduced lateral resolution and the absence of phase information in the lateral direction highly limit the accuracy in the computation of lateral displacements. In this context, this paper introduces a novel setup for the estimation of cardiac motion with ultrasound. The framework includes an unconventional beamforming technique and a dedicated motion estimation algorithm. The beamformer aims at introducing phase information in the lateral direction by producing transverse oscillations. The estimator directly exploits the phase information in the two directions by decomposing the image into two 2-D single-orthant analytic signals. An in silico evaluation of the proposed framework is presented on five ultra-realistic simulated echocardiographic sequences, where the proposed motion estimator is contrasted against other two phase-based solutions exploiting the presence of transverse oscillations and against block-matching on standard images. An implementation of the new beamforming strategy on a research ultrasound platform is also shown along with a preliminary in vivo evaluation on one healthy subject.

Ultrasound 2D Strain Estimator Based on Image Registration for Ultrasound Elastography

In this paper, we present a new approach to calculate 2D strain through the registration of the pre- and post-compression (deformation) B-mode image sequences based on an intensity-based non-rigid registration algorithm (INRA). Compared with the most commonly used cross-correlation (CC) method, our approach is not constrained to any particular set of directions, and can overcome displacement estimation errors introduced by incoherent motion and variations in the signal under high compression. This INRA method was tested using phantom and in vivo data. The robustness of our approach was demonstrated in the axial direction as well as the lateral direction where the standard CC method frequently fails. In addition, our approach copes well under large compression (over 6%). In the phantom study, we computed the strain image under various compressions and calculated the signal-to-noise (SNR) and contrast-to-noise (CNS) ratios. The SNR and CNS values of the INRA method were much higher than those calculated from the CC-based method. Furthermore, the clinical feasibility of our approach was demonstrated with the in vivo data from patients with arm lymphedema.

In vivo estimation of flexor digitorum superficialis tendon displacement with speckle tracking on 2-D ultrasound images using Laplacian, Gaussian and Rayleigh techniques

This study applies 2-D speckle tracking using B-scan ultrasound imaging to estimate the instantaneous and total displacement of the middle flexor digitorum superficialis (FDS) tendon proximal to the wrist. This is achieved by performing the study with human patients, during regular carpal tunnel surgeries. B-Scan images were collected with a 12-MHz transducer placed proximal to the wrist, while a video microscope simultaneously imaged the exposed flexor tendons in the palm as a reference for validation. The accuracy of the proposed speckle-based tracking method is compared using log-compressed Rayleigh (Fisher-Tippet)-, Gaussian (sum of squared differences)- and Laplacian (sum of absolute differences)-based statistics as similarity measures. Overall, tracking was successful and the Rayleigh technique performed better than the Laplacian or Gaussian technique. One goal of this research was to non-invasively monitor FDS tendon displacement in the wrist for the purposes of controlling a prosthetic device. An additional goal was to obtain pre- and post-operative clinical information.

4D-analysis of left ventricular heart cycle using procrustes motion analysis

The aim of this study is to investigate human left ventricular heart morphological changes in time among 17 healthy subjects. Preliminarily, 2 patients with volumetric overload due to aortic insufficiency were added to our analyses. We propose a special strategy to compare the shape, orientation and size of cardiac cycle's morphological trajectories in time. We used 3D data obtained by Speckle Tracking Echocardiography in order to detect semi-automated and homologous landmarks clouds as proxies of left ventricular heart morphology. An extended Geometric Morphometrics toolkit in order to distinguish between intra- and inter-individual shape variations was used. Shape of trajectories with inter-individual variation were compared under the assumption that trajectories attributes, estimated at electrophysiologically homologous times are expressions of left ventricular heart function. We found that shape analysis as commonly applied in Geometric Morphometrics studies fails in identifying a proper morpho-space to compare the shape of morphological trajectories in time. To overcome this problem, we performed a special type of Riemannian Parallel Transport, called "linear shift". Whereas the two patients with aortic insufficiency were not differentiated in the static shape analysis from the healthy subjects, they set apart significantly in the analyses of motion trajectory's shape and orientation. We found that in healthy subjects, the variations due to inter-individual morphological differences were not related to shape and orientation of morphological trajectories. Principal Component Analysis showed that volumetric contraction, torsion and twist are differently distributed on different axes. Moreover, global shape change appeared to be more correlated with endocardial shape change than with the epicardial one. Finally, the total shape variation occurring among different subjects was significantly larger than that observable across properly defined morphological trajectories.

Multi-resolution transverse oscillation in ultrasound imaging for motion estimation

Beyond all recent methods for estimating multidimensional motion vectors in ultrasound (US) image sequences, the transverse oscillation (TO) images coupled with a phase-based motion estimator has shown to be an extremely promising approach. To improve existing TO techniques, this paper proposes a multi-resolution transverse oscillation (MRTO) that measures the motion in US image sequences at different resolutions. Several TO images are created using harmonic images obtained from nonlinear US propagation or from composite emissions. Motion estimations are made with increasing resolution levels, i.e., decreasing transverse wavelength, to improve the previous measurements. When only lateral motion is applied to the tissue, the resulting estimations, quantitatively assessed in both simulations and in vitro experiments, are significantly improved in terms of mean motion error and standard deviation. With a 1-mm displacement in the chirp transmission, the error is reduced from 40.9% to 0.1% in the simulation and from 41.6% to 1.5% in the experiment. The first quasi-static elastography results, in simulation and experimentation, also confirm this improvement with an increased contrast-to-noise ratio and signal-to-noise ratio.

Methods for robust in vivo strain estimation in the carotid artery

A hierarchical block-matching motion tracking algorithm for strain imaging is presented. Displacements are estimated with improved robustness and precision by utilizing a Bayesian regularization algorithm and an unbiased subsample interpolation technique. A modified least-squares strain estimator is proposed to estimate strain images from a noisy displacement input while addressing the motion discontinuity at the wall-lumen boundary. Methods to track deformation over the cardiac cycle incorporate a dynamic frame skip criterion to process data frames with sufficient deformation to produce high signal-to-noise displacement and strain images. Algorithms to accumulate displacement and/or strain on particles in a region of interest over the cardiac cycle are described. New methods to visualize and characterize the deformation measured with the full 2D strain tensor are presented. Initial results from patients imaged prior to carotid endarterectomy suggest that strain imaging detects conditions that are traditionally considered high risk including soft plaque composition, unstable morphology, abnormal hemodynamics and shear of plaque against tethering tissue can be exacerbated by neoangiogenesis. For example, a maximum absolute principal strain exceeding 0.2 is observed near calcified regions adjacent to turbulent flow, protrusion of the plaque into the arterial lumen and regions of low echogenicity associated with soft plaques. Non-invasive carotid strain imaging is therefore a potentially useful tool for detecting unstable carotid plaque.

Longitudinal displacement of the carotid wall and cardiovascular risk factors: associations with aging, adiposity, blood pressure and periodontal disease independent of cross-sectional distensibility and intima-media thickness

The recently discovered longitudinal displacement of the common carotid arterial wall (i.e., the motion along the same plane as the blood flow), may be associated with incident cardiovascular events and represents a novel and relevant clinical information. At present, there have only been a few studies that have been conducted to investigate this longitudinal movement. We propose here a method to assess noninvasively the wall bi-dimensional (two-dimensional [2-D], cross-sectional and longitudinal) motion and present an original approach that combines a robust speckle tracking scheme to guidance by minimal path contours segmentation. Our method is well suited to large clinical population studies as it does not necessitate strong imaging prerequisites. The aim of this study is to describe the association between the longitudinal displacement of the carotid arterial wall and cardiovascular risk factors, among which periodontal disease. Some 126 Indigenous Australians with periodontal disease, an emerging risk factor, and 27 healthy age- and sex-matched non-indigenous control subjects had high-resolution ultrasound scans of the common carotid artery. Carotid intima-media thickness and arterial wall 2-D motion were then assessed using our method in ultrasound B-mode sequences. Carotid longitudinal displacement was markedly lower in the periodontal disease group than the control group (geometric mean (IQR): 0.15 mm (0.13) vs. 0.42 mm (0.30), respectively; p < 0.0001), independent of cardiovascular risk factors, cross-sectional distensibility and carotid intima-media thickness (p < 0.0001). A multivariable model indicated that the strongest correlates of carotid longitudinal displacement in adults with periodontal disease were age (β-coefficient = -.235, p = .03), waist (β-coefficient = -.357, p = 0.001), and pulse pressure (β-coefficient = .175, p = 0.07), independent of other cardiovascular risk factors, cross-sectional distensibility and pulse wave velocity. Carotid longitudinal displacement, estimated with our approach, is impaired in the periodontal disease group, independent of established cardiovascular risk factors and other noninvasive measures of arterial stiffness, and may represent an important marker of cardiovascular risk.

Strain-compounding technique with ultrasound Nakagami imaging for distinguishing between benign and malignant breast tumors

PURPOSE

The scatterer properties of breast tissues are related to the presence of collagen structures, while the elasticity properties of breast tissues depend on their structural organization; these two characteristics are functionally complementary in ultrasound-based tissue characterizations. This study investigated the use of a strain-compounding technique with Nakagami imaging to provide information associated with the scatterer and elasticity characteristics of tissues when attempting to identify benign and malignant breast tumors.

METHODS

The efficacy of the proposed method was tested by collecting raw data of ultrasound backscattered signals from 50 clinical cases (25 benign tumors and 25 malignant tumors, as verified by histology biopsies). The different strain conditions were created by applying manual compression. For each region in which breast tumors were suspected, estimates of the full width at half maximum (FWHM) from the Gaussian fitting curve for the Nakagami-parameter histogram in the strain-compounding Nakagami images were divided by those of the corresponding reference Nakagami images (uncompressed images); this parameter was denoted as the FWHM ratio. Receiver operating characteristic (ROC) curve analysis was adopted to assess the diagnostic performance.

RESULTS

The results demonstrated that the difference in scatterer distributions between before and after compounding was greater for benign tumors than for malignant tumors. The FWHM ratio estimates for benign and malignant tumors were 0.76 ± 0.14 and 0.96 ± 0.06 (mean ± standard deviation), respectively (p < 0.01). The mean area under the ROC curve using the FWHM ratio estimates was 0.92, with a 95% confidence interval of 0.83-1.00.

CONCLUSIONS

These findings indicate that the strain-compounding Nakagami imaging method based on the acquisition of multiple frames under different strain states could provide objective information that would improve the ability to classify benign and malignant breast tumors.

Regional cardiac motion and strain estimation in three-dimensional echocardiography: a validation study in thick-walled univentricular phantoms

Automatic quantification of regional left ventricular deformation in volumetric ultrasound data remains challenging. Many methods have been proposed to extract myocardial motion, including techniques using block matching, phase-based correlation, differential optical flow methods, and image registration. Our lab previously presented an approach based on elastic registration of subsequent volumes using a B-spline representation of the underlying transformation field. Encouraging results were obtained for the assessment of global left ventricular function, but a thorough validation on a regional level was still lacking. For this purpose, univentricular thick-walled cardiac phantoms were deformed in an experimental setup to locally assess strain accuracy against sonomicrometry as a reference method and to assess whether regions containing stiff inclusions could be detected. Our method showed good correlations against sonomicrometry: r(2) was 0.96, 0.92, and 0.84 for the radial (ε(RR)), longitudinal (ε(LL)), and circumferential (ε(CC)) strain, respectively. Absolute strain errors and strain drift were low for ε(LL) (absolute mean error: 2.42%, drift: -1.05%) and ε(CC) (error: 1.79%, drift: -1.33%) and slightly higher for ε(RR) (error: 3.37%, drift: 3.05%). The discriminative power of our methodology was adequate to resolve full transmural inclusions down to 17 mm in diameter, although the inclusion-to-surrounding tissue stiffness ratio was required to be at least 5:2 (absolute difference of 39.42 kPa). When the inclusion-to-surrounding tissue stiffness ratio was lowered to approximately 2:1 (absolute difference of 22.63 kPa), only larger inclusions down to 27 mm in diameter could still be identified. Radial strain was found not to be reliable in identifying dysfunctional regions.

Estimating elastogram series of different resolutions using a multiresolution strain computation method

The techniques used to estimate axial elastogram usually present a trade-off between elastogram resolution and noise level. It is advantageous to format a series of elastograms of various resolutions because each can provide different information about tissue stiffness. This goal is traditionally achieved by generating displacement fields using various window lengths, which increases computation load significantly. In this study, we achieve the same goal by using a multiresolution strain computation method based on Savitzky-Golay digital differentiators of different lengths, which requires calculating the displacement field only once. Simulation and experimental results show that the elastograms estimated by the proposed method are comparable to those estimated by traditional methods in terms of resolution, elastographic signal-to-noise ratio, and elastographic contrast-to-noise ratio, but the proposed method requires significantly less computational time.

Analysis of 2-D motion tracking in ultrasound with dual transducers

We study displacement and strain measurement error of dual transducers (two linear arrays, aligned orthogonally and coplanar). Displacements along the beam of each transducer are used to obtain measurements in two-dimensions. Simulations (5MHz) and experiments (10MHz) are compared to measurements with a single linear array, with and without angular compounding. Translation simulations demonstrate factors of 1.07 larger and 8.0 smaller biases in the axial and lateral directions respectively, for dual transducers compared to angular compounding. As the angle between dual transducers decreases from 90° to 40°, for 1% compression simulations, the lateral RMS error ranges from 2.1 to 3.9μm compared to 9μm with angular compounding. Simulation of dual transducer misalignment of 1mm and 2° result in errors of less than 9μm. Experiments demonstrate factors of 3.0 and 5.2 lower biases for dual transducers in the axial and lateral directions respectively compared to angular compounding.

Measurement of two-dimensional movement parameters of the carotid artery wall for early detection of arteriosclerosis: a preliminary clinical study

The aim of this study was to clinically investigate the association between the risk factors of early-stage atherosclerosis and the two-dimensional (2-D) movement of the artery wall. To meet this objective, a speckle tracking approach for the estimation of the 2-D trajectory of the vessel wall was proposed and applied to B-mode ultrasound (US) sequences of the left common carotid artery (CCA). A deformable skeleton model was also introduced in the block matching scheme. Finally, the 2-D movements of both proximal and distal walls were investigated in three different local regions, with 1.5 × 0.3 mm(2) kernel blocks. A clinical study was conducted in which two different populations (26 young healthy volunteers and 26 older diabetic patients) were studied. The results show that the mean amplitude value of the diameter change ΔD, of the longitudinal displacement of the proximal wall ΔX(p) and of the longitudinal displacement of the distal wall ΔX(d) were 0.65 ± 0.17 vs. 0.41 ± 0.12 mm (p < 0.001), 0.48 ± 0.21 vs. 0.26 ± 0.18 mm (p < 0.001) and 0.48 ± 0.20 vs. 0.35 ± 0.23 mm (p = 0.006) for the young healthy volunteers and the older diabetic patients, respectively. The results of the three dynamic parameters ΔD, ΔX(p) and ΔX(d) were systematically and significantly lower for the diabetic subjects, respectively 37%, 46% and 27%. The method introduced in this feasibility study might constitute a pertinent approach to assess the presence of early-stage arteriosclerosis by the noninvasive estimation of the 2-D motion of the intima-media complex in the CCA.

Real-time quasi-static ultrasound elastography

Ultrasound elastography is a technique used for clinical imaging of tissue stiffness with a conventional ultrasound machine. It was first proposed two decades ago, but active research continues in this area to the present day. Numerous clinical applications have been investigated, mostly related to cancer imaging, and though these have yet to prove conclusive, the technique has seen increasing commercial and clinical interest. This paper presents a review of the most widely adopted, non-quantitative, techniques focusing on technical innovations rather than clinical applications. The review is not intended to be exhaustive, concentrating instead on placing the various techniques in context according to the authors' perspective of the field.

Torsion of the human left ventricle: experimental analysis and computational modeling

We set a twofold investigation: we assess left ventricular (LV) rotation and twist in the human heart through 3D-echocardiographic speckle tracking, and use representative experimental data as benchmark with respect to numerical results obtained by solving our mechanical model of the LV. We aim at new insight into the relationships between myocardial contraction patterns and the overall behavior at the scale of the whole organ. It is concluded that torsional rotation is sensitive to transmural gradients of contractility which is assumed linearly related to action potential duration (APD). Pressure-volume loops and other basic strain measures are not affected by these gradients. Therefore, realistic torsional behavior of human LV may indeed correspond to the electrophysiological and functional differences between endocardial and epicardial cells recently observed in non-failing hearts. Future investigations need now to integrate the mechanical model proposed here with minimal models of human ventricular APD to drive excitation-contraction coupling transmurally.

Bayesian regularization applied to ultrasound strain imaging

Noise artifacts due to signal decorrelation and reverberation are a considerable problem in ultrasound strain imaging. For block-matching methods, information from neighboring matching blocks has been utilized to regularize the estimated displacements. We apply a recursive Bayesian regularization algorithm developed by Hayton et al. [Artif. Intell., vol. 114, pp. 125-156, 1999] to phase-sensitive ultrasound RF signals to improve displacement estimation. The parameter of regularization is reformulated, and its meaning examined in the context of strain imaging. Tissue-mimicking experimental phantoms and RF data incorporating finite-element models for the tissue deformation and frequency-domain ultrasound simulations are used to compute the optimal parameter with respect to nominal strain and algorithmic iterations. The optimal strain regularization parameter was found to be twice the nominal strain and did not vary significantly with algorithmic iterations. The technique demonstrates superior performance over median filtering in noise reduction at strains 5% and higher for all quantitative experiments performed. For example, the strain SNR was 11 dB higher than that obtained using a median filter at 7% strain. It has to be noted that for applied deformations lower than 1%, since signal decorrelation errors are minimal, using this approach may degrade the displacement image.

Left ventricular border tracking using cardiac motion models and optical flow

The use of automated methods is becoming increasingly important for assessing cardiac function quantitatively and objectively. In this study, we propose a method for tracking three-dimensional (3-D) left ventricular contours. The method consists of a local optical flow tracker and a global tracker, which uses a statistical model of cardiac motion in an optical-flow formulation. We propose a combination of local and global trackers using gradient-based weights. The algorithm was tested on 35 echocardiographic sequences, with good results (surface error: 1.35 ± 0.46 mm, absolute volume error: 5.4 ± 4.8 mL). This demonstrates the method's potential in automated tracking in clinical quality echocardiograms, facilitating the quantitative and objective assessment of cardiac function.

Real-time regularized ultrasound elastography

This paper introduces two real-time elastography techniques based on analytic minimization (AM) of regularized cost functions. The first method (1D AM) produces axial strain and integer lateral displacement, while the second method (2D AM) produces both axial and lateral strains. The cost functions incorporate similarity of radio-frequency (RF) data intensity and displacement continuity, making both AM methods robust to small decorrelations present throughout the image. We also exploit techniques from robust statistics to make the methods resistant to large local decorrelations. We further introduce Kalman filtering for calculating the strain field from the displacement field given by the AM methods. Simulation and phantom experiments show that both methods generate strain images with high SNR, CNR and resolution. Both methods work for strains as high as 10% and run in real-time. We also present in vivo patient trials of ablation monitoring. An implementation of the 2D AM method as well as phantom and clinical RF-data can be downloaded.

Comparison of 2-D speckle tracking and tissue Doppler imaging in an isolated rabbit heart model

Ultrasound strain imaging has been proposed to quantitatively assess myocardial contractility. Cross-correlation-based 2-D speckle tracking (ST) and auto-correlation-based tissue Doppler imaging (TDI) [often called Doppler tissue imaging (DTI)] are competitive ultrasound techniques for this application. Compared with 2-D ST, TDI, as a 1-D method, is sensitive to beam angle and suffers from low strain signal-to-noise ratio because a high pulse repetition frequency is required to avoid aliasing in velocity estimation. In addition, ST and TDI are fundamentally different in the way that physical parameters such as the mechanical strain are derived, resulting in different estimation accuracy and interpretation. In this study, we directly compared the accuracy of TDI and 2-D ST estimates of instantaneous axial normal strain and accumulated axial normal strain using a simulated heart. We then used an isolated rabbit heart model of acute ischemia produced by left descending anterior artery ligation to evaluate the performance of the two methods in detecting abnormal motion. Results showed that instantaneous axial normal strains derived using TDI (0.36% error) were less accurate with larger variance than those derived from 2-D ST (0.08% error) given the same spatial resolution. In addition to poorer accuracy, accumulated axial normal strain estimates derived using TDI suffered from bias, because the accumulation method for TDI cannot trace along the actual tissue displacement path. Finally, we demonstrated the advantage 2-D ST has over TDI to reduce dependency on beam angle for lesion detection by estimating strains based on the principal stretches and their corresponding principal axes.

A motion estimation refinement framework for real-time tissue axial strain estimation with freehand ultrasound

Ultrasound elastography has become a wellknown optional imaging method for the diagnosis of tissue abnormalities in various body parts. It images the elasticity of compliant tissues by estimating the local displacements and strains using pre- and post-compression RF echo signals. In this paper, taking the RF signal as image intensity and RF samples as pixels, we present a motion estimation framework to compute the axial tissue displacements and strains. This method takes advantage of both the block matching algorithm (BMA) and local optical flow techniques. For two frames of RF signals, coarse motion estimates are first computed using BMA. The motion estimates obtained are then used to warp the first frame toward the second one, thus making the warped frame more spatially correlated to the second one. Next, the Lucas-Kanade optical flow method is employed to compute the residual motion between the warped frame and the original second frame, with inherent sub-pixel precision. Finally, the displacements from the two steps are combined. The warp-and-refine procedure can be iterated if the residual motion is larger than a predefined empirical threshold. To test its feasibility, we first applied the method to simulated data. The results show that our method is robust to relatively large motions and is capable of generating accurate motion estimation with subsample spatial resolution. These methods have been deployed and are being tested on a commercialized ultrasound machine that previously did not have elastography functions. Quality real-time display of elastography along with freehand scanning has been accomplished. The proposed framework provides an alternative method for motion estimation with good performance, and it can potentially be improved using hardware to realize the BMA.

A hybrid displacement estimation method for ultrasonic elasticity imaging

Axial displacement estimation is fundamental to many freehand quasistatic ultrasonic strain imaging systems. In this paper, we present a novel estimation method that combines the strengths of quality-guided tracking, multi-level correlation, and phase-zero search to achieve high levels of accuracy and robustness. The paper includes a full description of the hybrid method, in vivo examples to illustrate the method's clinical relevance, and finite element simulations to assess its accuracy. Quantitative and qualitative comparisons are made with leading single- and multi-level alternatives. In the in vivo examples, the hybrid method produces fewer obvious peak-hopping errors, and in simulation, the hybrid method is found to reduce displacement estimation errors by 5 to 50%. With typical clinical data, the hybrid method can generate more than 25 strain images per second on commercial hardware; this is comparable with the alternative approaches considered in this paper.

3-D phantom and in vivo cardiac speckle tracking using a matrix array and raw echo data

Cardiac motion has been tracked using various methods, which vary in their invasiveness and dimensionality. One such noninvasive modality for cardiac motion tracking is ultrasound. Three-dimensional ultrasound motion tracking has been demonstrated using detected data at low volume rates. However, the effects of volume rate, kernel size, and data type (raw and detected) have not been sufficiently explored. First comparisons are made within the stated variables for 3-D speckle tracking. Volumetric data were obtained in a raw, baseband format using a matrix array attached to a high parallel receive beam count scanner. The scanner was used to acquire phantom and human in vivo cardiac volumetric data at 1000-Hz volume rates. Motion was tracked using phase-sensitive normalized cross-correlation. Subsample estimation in the lateral and elevational dimensions used the grid-slopes algorithm. The effects of frame rate, kernel size, and data type on 3-D tracking are shown. In general, the results show improvement of motion estimates at volume rates up to 200 Hz, above which they become stable. However, peak and pixel hopping continue to decrease at volume rates higher than 200 Hz. The tracking method and data show, qualitatively, good temporal and spatial stability (for independent kernels) at high volume rates.

Analysis of motion tracking in echocardiographic image sequences: influence of system geometry and point-spread function

This paper focuses on motion tracking in echocardiographic ultrasound images. The difficulty of this task is related to the fact that echographic image formation induces decorrelation between the underlying motion of tissue and the observed speckle motion. Since Meunier's seminal work, this phenomenon has been investigated in many simulation studies as part of speckle tracking or optical flow-based motion estimation techniques. Most of these studies modeled image formation using a linear convolution approach, where the system point-spread function (PSF) was spatially invariant and the probe geometry was linear. While these assumptions are valid over a small spatial area, they constitute an oversimplification when a complete image is considered. Indeed, echocardiographic acquisition geometry relies on sectorial probes and the system PSF is not perfectly invariant, even if dynamic focusing is performed. This study investigated the influence of sectorial geometry and spatially varying PSF on speckle tracking. This was done by simulating a typical 64 elements, cardiac probe operating at 3.5 MHz frequency, using the simulation software Field II. This simulation first allowed quantification of the decorrelation induced by the system between two images when simple motion such as translation or incompressible deformation was applied. We then quantified the influence of decorrelation on speckle tracking accuracy using a conventional block matching (BM) algorithm and a bilinear deformable block matching (BDBM) algorithm. In echocardiography, motion estimation is usually performed on reconstructed images where the initial sectorial (i.e., polar) data are interpolated on a cartesian grid. We therefore studied the influence of sectorial acquisition geometry, by performing block matching on cartesian and polar data. Simulation results show that decorrelation is spatially variant and depends on the position of the region where motion takes place relative to the probe. Previous studies did not consider translation in their experiments, since their simulation model (spatially invariant PSF and linear probe) yields by definition no decorrelation. On the opposite, our realistic simulation settings (i.e., sectorial probe and realistic beamforming) show that translation yields decorrelation, particularly when translation is large (above 6 mm) and when the moving regions is located close to the probe (distance to probe less than 50 mm). The tracking accuracy study shows that tracking errors are larger for the usual cartesian data, whatever the estimation algorithm, indicating that speckle tracking is more reliable when based on the unconverted polar data: for axial translations in the range 0-10 mm, the maximum error associated to conventional block matching (BM) is 4.2 mm when using cartesian data and 1.8 mm for polar data. The corresponding errors are 1.8 mm (cartesian data) and 0.4 mm (polar data) for an applied deformation in the range 0-10%. We also show that accuracy is improved by using the bilinear deformable block matching (BDBM) algorithm. For translation, the maximum error associated to the bilinear deformable block matching is indeed 3.6mm (cartesian data) and 1.2 mm (polar data). Regarding deformation, the error is 0.7 mm (cartesian data) and 0.3 mm (polar data). These figures also indicates that the larger improvement brought by the bilinear deformable block matching over standard block matching logically takes place when deformation on cartesian data is considered (the error drops from 1.8 to 0.7 mm is this case). We give a preliminary evaluation of this framework on a cardiac sequence acquired with a Toshiba Powervision 6000 imaging system using a probe operating at 3.25 MHz. As ground truth reference motion is not available in this case, motion estimation performance was evaluated by comparing a reference image (i.e., the first image of the sequence) and the subsequent images after motion compensation has been applied. The comparison was quantified by computing the normalized correlation between the reference and the motion-compensated images. The obtained results are consistent with the simulation data: correlation is smaller for cartesian data, whatever the estimation algorithm. The correlation associated to the conventional block matching (BM) is in the range 0.45-0.02 when using cartesian data and in the range 0.65-0.2 for polar data. The corresponding correlation ranges for the bilinear deformable block matching are 0.98-0.2 and 0.98-0.55. In the same way these figures indicate that the bilinear deformable block matching yield a larger improvement when cartesian data are considered (correlation range increases from 0.45-0.02 to 0.98-0.2 in this case).

A generalized speckle tracking algorithm for ultrasonic strain imaging using dynamic programming

This study developed an improved motion estimation algorithm for ultrasonic strain imaging that employs a dynamic programming technique. In this article, we model the motion estimation task as an optimization problem. Since tissue motion under external mechanical stimuli often should be reasonably continuous, a set of cost functions combining correlation and various levels of motion continuity constraint were used to regularize the motion estimation. To solve the optimization problem with a reasonable computational load, a dynamic programming technique that does not require iterations was used to obtain displacement vectors in integer precision. Then, a subsample estimation algorithm was used to calculate local displacements in fractional precision. Two implementation schemes were investigated with in vivo ultrasound echo data sets. We found that the proposed algorithm provides more accurate displacement estimates than our previous algorithm for in vivo clinical data. In particular, the new algorithm is capable of tracking motion in more complex anatomy and increases strain image consistency in a sequence of images. Preliminary results also suggest that a significantly longer sequence of high contrast strain images could be obtained with the new algorithm compared with the previous algorithm. The new algorithm can also tolerate larger motion discontinuities (e.g., cavity in an anthropomorphic uterine phantom).