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

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

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

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

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

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

Speckle coherence of piecewise-stationary stochastic targets.

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

Multi-covariate Imaging of Sub-resolution Targets.

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

Sonic Estimation of Elasticity via Resonance: A New Method of Assessing Hemostasis.

Uncontrolled bleeding threatens patients undergoing major surgery and in care for traumatic injury. This paper describes a novel method of diagnosing coagulation dysfunction by repeatedly measuring the shear modulus of a blood sample as it clots in vitro. Each measurement applies a high-energy ultrasound pulse to induce a shear wave within a rigid walled chamber, and then uses low energy ultrasound pulses to measure displacements associated with the resonance of that shear wave. Measured displacements are correlated with predictions from finite difference time domain models, with the best fit corresponding to the modulus estimate. In our current implementation each measurement requires 62.4 ms. Experimental data was analyzed using a fixed-viscosity algorithm and a free-viscosity algorithm. In experiments utilizing human blood induced to clot by exposure to kaolin, the free-viscosity algorithm quantified the shear modulus of formed clots with a worst-case precision of 2.5%. Precision was improved to 1.8% by utilizing the fixed-viscosity algorithm. Repeated measurements showed a smooth evolution from liquid blood to a firm clot with a shear modulus between 1.4 and 3.3 kPa. These results show the promise of this technique for rapid, point of care assessment of coagulation.

Sonorheometry assessment of platelet function in cardiopulmonary bypass patients: Correlation of blood clot stiffness with platelet integrin αIIbß3 activity, aspirin usage, and transfusion risk.

BACKGROUND: Impaired platelet function may underlie bleeding associated with cardiopulmonary bypass (CPB) and at present is incompletely evaluated with existing diagnostic technologies. Sonorheometry (SR) is a recently developed ultrasound-based technology that quantifies hemostasis and platelet activity from a blood sample by measuring ex vivo clot stiffness (S). We hypothesized that impaired platelet-fibrin interactions as assessed by SR would correlate with transfusion during CPB and history of prior aspirin therapy. METHODS: Thirty-nine patients undergoing elective cardiopulmonary bypass (CPB) were enrolled following informed consent (University of Virginia IRB#14050) in a prospective observational pilot study to assess pre-operative platelet function and transfusion frequency. To assess platelet activity, abciximab was added to blood prior to SR and native S versus abciximab treated S created a differential test for platelet activity. Patient blood samples were activated with kaolin and SR was then used to measure clot stiffness. Patients were transfused with blood products as directed by clinical practice, with the surgical team blinded to SR results. RESULTS: Blood clot stiffness with and without abciximab, was compared in a ratio test (S/Sabciximab) named the Platelet Function Index (PFI). PFI was hypothesized to be positively correlated with platelet contributions through integrin αIIbß3 to clot stiffness. PFI for CPB subjects was lower for those receiving transfusions than those not receiving transfusions (p<0.006). A receiver-operator characteristics (ROC) analysis correlating the PFI with the blinded surgical team's decision on transfusions that included platelet concentrates generated an area under the curve (AUC) of 0.79 (p<0.001). Additionally, the mean value of PFI for subjects on aspirin therapy was lower than for those not on aspirin therapy (p<0.02) and correlated with a 1.73-fold enhanced risk of receiving a peri-operative transfusion. CONCLUSION: Evaluation of platelet function with SR may help in the specification of blood transfusion needs in cardiac surgery and in the assessment of aspirin effects on risk of surgical bleeding.

Broadband optimal contrast resolution beamforming.

This paper proposes a novel receive beamformer architecture for broadband imaging systems that uses unique finite impulse response (FIR) filters on each channel. The conventional delay-and-sum (DAS) beamformer applies receive apodization by weighting the signal on each receive channel prior to beam summation. Our proposed FIR beamformer passes the focused receive radio frequency (RF) signals through multi-tap FIR filters on each receive channel prior to summation. The receive FIR filters are constructed to maximize the contrast resolution of the system's spatial response. The broadband FIR beamformer produces spatial point spread functions (PSFs) with narrower mainlobe widths and lower sidelobe levels than spatial PSFs produced by the conventional DAS beamformer. We present simulation results showing that FIR filters of modest tap lengths (3-7) can yield marked improvement in image contrast and point resolution. Specifically we show that 7-tap FIR filters can reduce sidelobe and grating lobe energy by 30dB and improve contrast resolution by as much as 20dB compared to conventional apodization profiles. This improvement in contrast resolution comes at the expense of a decrease in beamformer sensitivity. We investigate the effects of phase aberration and show in simulation results that the multi-tap FIR beamformer outperforms the unaberrated DAS beamformer by 8-12dB even in the presence of moderate aberration characterized by a root-mean-square strength of 28ns and a full-width at half-maximum correlation length of 3.6mm. We show experimental results wherein multi-tap FIR filters decrease sidelobe energy in the resulting 2D spatial response while achieving a narrow mainlobe. We also show results where the FIR beamformer improves the contrast to noise ratio (CNR) in simulated B-mode cyst images by more than 4dB. Our algorithm has the potential to significantly improve ultrasound beamforming in any application where the system response is reasonably well characterized. Furthermore, this algorithm can be used to increase contrast and resolution in one-way beamforming systems such as acousto-optic and opto-acoustic imaging.

Complex principal components for robust motion estimation.

Bias and variance errors in motion estimation result from electronic noise, decorrelation, aliasing, and inherent algorithm limitations. Unlike most error sources, decorrelation is coherent over time and has the same power spectrum as the signal. Thus, reducing decorrelation is impossible through frequency domain filtering or simple averaging and must be achieved through other methods. In this paper, we present a novel motion estimator, termed the principal component displacement estimator (PCDE), which takes advantage of the signal separation capabilities of principal component analysis (PCA) to reject decorrelation and noise. Furthermore, PCDE only requires the computation of a single principal component, enabling computational speed that is on the same order of magnitude or faster than the commonly used Loupas algorithm. Unlike prior PCA strategies, PCDE uses complex data to generate motion estimates using only a single principal component. The use of complex echo data is critical because it allows for separation of signal components based on motion, which is revealed through phase changes of the complex principal components. PCDE operates on the assumption that the signal component of interest is also the most energetic component in an ensemble of echo data. This assumption holds in most clinical ultrasound environments. However, in environments where electronic noise SNR is less than 0 dB or in blood flow data for which the wall signal dominates the signal from blood flow, the calculation of more than one PC is required to obtain the signal of interest. We simulated synthetic ultrasound data to assess the performance of PCDE over a wide range of imaging conditions and in the presence of decorrelation and additive noise. Under typical ultrasonic elasticity imaging conditions (0.98 signal correlation, 25 dB SNR, 1 sample shift), PCDE decreased estimation bias by more than 10% and standard deviation by more than 30% compared with the Loupas method and normalized cross-correlation with cosine fitting (NC CF). More modest gains were observed relative to spline-based time delay estimation (sTDE). PCDE was also tested on experimental elastography data. Compressions of approximately 1.5% were applied to a CIRS elastography phantom with embedded 10.4-mm-diameter lesions that had moduli contrasts of -9.2, -5.9, and 12.0 dB. The standard deviation of displacement estimates was reduced by at least 67% in homogeneous regions at 35 to 40 mm in depth with respect to estimates produced by Loupas, NC CF, and sTDE. Greater improvements in CNR and displacement standard deviation were observed at larger depths where speckle decorrelation and other noise sources were more significant.

Super-resolution image reconstruction using diffuse source models.

Image reconstruction is central to many scientific fields, from medical ultrasound and sonar to computed tomography and computer vision. Although lenses play a critical reconstruction role in these fields, digital sensors enable more sophisticated computational approaches. A variety of computational methods have thus been developed, with the common goal of increasing contrast and resolution to extract the greatest possible information from raw data. This paper describes a new image reconstruction method named the Diffuse Time-domain Optimized Near-field Estimator (dTONE). dTONE represents each hypothetical target in the system model as a diffuse region of targets rather than a single discrete target, which more accurately represents the experimental data that arise from signal sources in continuous space, with no additional computational requirements at the time of image reconstruction. Simulation and experimental ultrasound images of animal tissues show that dTONE achieves image resolution and contrast far superior to those of conventional image reconstruction methods. We also demonstrate the increased robustness of the diffuse target model to major sources of image degradation through the addition of electronic noise, phase aberration and magnitude aberration to ultrasound simulations. Using experimental ultrasound data from a tissue-mimicking phantom containing a 3-mm-diameter anechoic cyst, the conventionally reconstructed image has a cystic contrast of -6.3 dB, whereas the dTONE image has a cystic contrast of -14.4 dB.

Adaptive force sonorheometry for assessment of whole blood coagulation.

BACKGROUND: Viscoelastic diagnostics that monitor the hemostatic function of whole blood (WB), such as thromboelastography, have been developed with demonstrated clinical utility. By measuring the cumulative effects of all components of hemostasis, viscoelastic diagnostics have circumvented many of the challenges associated with more common tests of blood coagulation. METHODS: We describe a new technology, called sonorheometry, that adaptively applies acoustic radiation force to assess coagulation function in WB. The repeatability (precision) of coagulation parameters was assessed using citrated WB samples. A reference range of coagulation parameters, along with corresponding measurements from prothrombin time (PT) and partial thromboplastin time (PTT), were obtained from WB samples of 20 healthy volunteers. In another study, sonorheometry monitored anticoagulation with heparin (0-5 IU/ml) and reversal from varied dosages of protamine (0-10 IU/ml) in heparinized WB (2 IU/ml). RESULTS: Sonorheometry exhibited low CVs for parameters: clot initiation time (TC1), <7%; clot stabilization time (TC2), <6.5%; and clotting angle (theta), <3.5%. Good correlation was observed between clotting times, TC1 and TC2, and PTT (r=0.65 and 0.74 respectively; n=18). Linearity to heparin dosage was observed with average linearity r>0.98 for all coagulation parameters. We observed maximum reversal of heparin anticoagulation at protamine to heparin ratios of 1.4:1 from TC1 (P=0.6) and 1.2:1 from theta (P=0.55). CONCLUSIONS: Sonorheometry is a non-contact method for precise assessment of WB coagulation.

A novel ultrasound-based method to evaluate hemostatic function of whole blood.

BACKGROUND: Unregulated hemostasis represents a leading cause of mortality and morbidity in the developed world. Being able to recognize and quantify defects of the hemostatic process is critical to reduce mortality and implement appropriate treatment. METHODS: We describe a novel ultrasound-based technology, named sonorheometry, which can assess hemostasis function from a small sample of blood. Sonorheometry uses the phenomenon of acoustic radiation force to measure the dynamic changes in blood viscoelasticity during clot formation and clot dissolution. We performed in vitro experiments using whole blood samples of 1 ml to demonstrate that sonorheometry is indicative of hemostatic functions that depend on plasma coagulation factors, platelets, and plasma fibrinolytic factors. RESULTS: Sonorheometry measurements show titration effects to compounds known to alter the coagulation factors (GPRP peptide, 0 to 8 mmol/l), platelets (abciximab, 0 to 12 microg/ml), and fibrinolytic factors (urokinase, 0 to 200 U). Repeated measurements of blood samples from the same subjects yielded reproducibility errors on the order of 5%. CONCLUSIONS: These data indicate that sonorheometry accurately quantifies the functional role of the components of hemostasis in vitro.

Robust finite impulse response beamforming applied to medical ultrasound.

We previously described a beamformer architecture that replaces the single apodization weights on each receive channel with channel-unique finite impulse response (FIR) filters. The filter weights are designed to optimize the contrast resolution performance of the imaging system. Although the FIR beamformer offers significant gains in contrast resolution, the beamformer suffers from low sensitivity, and its performance rapidly degrades in the presence of noise. In this paper, a new method is presented to improve the robustness of the FIR beamformer to electronic noise as well as variation or uncertainty in the array response. A method is also described that controls the sidelobe levels of the FIR beamformer's spatial response by applying an arbitrary weighting function in the filter design algorithm. The robust FIR beamformer is analyzed using a generalized cystic resolution metric that quantifies a beamformer's clinical imaging performance as a function of cyst size and channel input SNR. Fundamental performance limits are compared between 2 robust FIR beamformers - the dynamic focus FIR (DF-FIR) beamformer and the group focus FIR (GF-FIR) beamformer - the conventional delay-and-sum (DAS) beamformer, and the spatial-matched filter (SMF) beamformer. Results from this study show that the new DF- and GF-FIR beamformers are more robust to electronic noise compared with the optimal contrast resolution FIR beamformer. Furthermore, the added robustness comes with only a slight loss in cystic resolution. Results from the generalized cystic resolution metric show that a 9-tap robust FIR beamformer outperforms the SMF and DAS beamformer until receive channel input SNR drops below -5 dB, whereas the 9-tap optimal contrast resolution beamformer's performance deteriorates around 50 dB SNR. The effects of moderate phase aberrations, characterized by an a priori root-mean-square strength of 28 ns and an a priori full-width at half-maximum correlation length of 3.6 mm, are investigate- d on the robust FIR beamformers. Full sets of robust FIR beamformer filter weights are constructed using an in silico model scanner and the L14-5/38 mm probe. Using the derived weights, a series of simulated point target and anechoic cyst B-mode images are generated to investigate further the potential increases in contrast resolution when using the robust FIR beamformers. Under the investigated conditions, the 7-tap optimal contrast resolution beamformer and the 7-tap robust beamformer with added SNR constraint increase lesion detectability by 247 and 137% compared with the conventional DAS beamformer, respectively. Finally, experimental phantom and in vivo images are produced using this novel receive architecture. The simulated and experimental images clearly show a reduction in clutter and an increase in contrast resolution compared with the conventionally beamformed images. This novel receive beamformer can be applied to any conventional ultrasound system where the system response is reasonably well characterized.

Reduction of echo decorrelation via complex principal component filtering.

Ultrasound motion estimation is a fundamental component of clinical and research techniques that include color flow Doppler, spectral Doppler, radiation force imaging and ultrasound-based elasticity estimation. In each of these applications, motion estimates are corrupted by signal decorrelation that originates from nonuniform target motion across the acoustic beam. In this article, complex principal component filtering (PCF) is demonstrated as a filtering technique for dramatically reducing echo decorrelation in blood flow estimation and radiation force imaging. We present simulation results from a wide range of imaging conditions that illustrate a dramatic improvement over simple bandpass filtering in terms of overall echo decorrelation (< or =99.9% reduction), root mean square error (< or =97.3% reduction) and the standard deviation of displacement estimates (< or =97.4% reduction). A radiation force imaging technique, termed sonorheometry, was applied to fresh whole blood during coagulation, and complex PCF operated on the returning echoes. Sonorheometry was specifically chosen as an example radiation force imaging technique in which echo decorrelation corrupts motion estimation. At 2 min after initiation of blood coagulation, the average echo correlation for sonorheometry improved from 0.996 to 0.9999, which corresponded to a 41.0% reduction in motion estimation variance as predicted by the Cramer-Rao lower bound under reasonable imaging conditions. We also applied complex PCF to improve blood velocity estimates from the left carotid artery of a healthy 23-year-old male. At the location of peak blood velocity, complex PCF improved the correlation of consecutive echo signals from an average correlation of 0.94 to 0.998. The improved echo correlation for both sonorheometry and blood flow estimation yielded motion estimates that exhibited more consistent responses with less noise. Complex PCF reduces speckle decorrelation and improves the performance of ultrasonic motion estimation.

Generalized cystic resolution: a metric for assessing the fundamental limits on beamformer performance.

Existing methods for characterizing the imaging performance of ultrasound systems do not clearly quantify the impact of contrast, spatial resolution, and signal-to-noise ratio (SNR). Although the beamplot, contrast resolution metrics, SNR measurements, ideal observer methods, and contrast-detail analysis provide useful information, it remains difficult to discern how changes in system parameters affect these metrics and clinical imaging performance. In this paper, we present a rigorous methodology for characterizing the pulse-echo imaging performance of arbitrary ultrasound systems. Our metric incorporates the 4-D spatio-temporal system response, which is defined as a function of the individual beamformer channel weights. The metric also incorporates the individual beamformer channel electronic SNR. Whereas earlier performance measures dealt solely with contrast resolution or echo signal-to-noise ratio, our metric combines them so that tradeoffs between these parameters are easily distinguishable. The new metric quantifies an arbitrary system's contrast resolution and SNR performance as a function of cyst size, beamformer channel weights, and beamformer channel SNR. We present a theoretical derivation of the unified performance metric and provide simulation and experimental results highlighting the metric's utility. We compare the fundamental performance limits of 2 beamforming strategies: the dynamic focus finite impulse response (FIR) filter beamformer and the spatial matched filter (SMF) beamformer to the performance of the conventional delay-and-sum (DAS) beamformer. Results from this study show that the SMF beamformer and the FIR beamformer offer significant gains in beamformer SNR and contrast resolution compared with the DAS beamformer, respectively. The metric clearly distinguishes the performance of the SMF beamformer, which enhances system sensitivity, from the FIR beamformer, which optimizes system contrast resolution. Finally, the metric provides one quantitative goal for optimizing a broadband beamformer?s contrast resolution performance.

A method for accurate in silico modeling of ultrasound transducer arrays.

This paper presents a new approach to improve the in silico modeling of ultrasound transducer arrays. While current simulation tools accurately predict the theoretical element spatio-temporal pressure response, transducers do not always behave as theorized. In practice, using the probe's physical dimensions and published specifications in silico, often results in unsatisfactory agreement between simulation and experiment. We describe a general optimization procedure used to maximize the correlation between the observed and simulated spatio-temporal response of a pulsed single element in a commercial ultrasound probe. A linear systems approach is employed to model element angular sensitivity, lens effects, and diffraction phenomena. A numerical deconvolution method is described to characterize the intrinsic electro-mechanical impulse response of the element. Once the response of the element and optimal element characteristics are known, prediction of the pressure response for arbitrary apertures and excitation signals is performed through direct convolution using available tools. We achieve a correlation of 0.846 between the experimental emitted waveform and simulated waveform when using the probe's physical specifications in silico. A far superior correlation of 0.988 is achieved when using the optimized in silico model. Electronic noise appears to be the main effect preventing the realization of higher correlation coefficients. More accurate in silico modeling will improve the evaluation and design of ultrasound transducers as well as aid in the development of sophisticated beamforming strategies.

Computationally efficient spline-based time delay estimation.

We previously presented a highly accurate, spline-based time delay estimator that directly determines subsample time delay estimates from sampled data. The algorithm uses cubic splines to produce a continuous time representation of a reference signal, and then computes an analytical matching function between this reference and a delayed signal. The location of the minima of this function yields estimates of the time delay. In this paper we present more computationally efficient formulations of this algorithm. We present the results of computer simulations and ultrasound experiments which indicate that the bias and the standard deviation of the proposed algorithms are comparable to those of the original method, and thus superior to other published algorithms.

MUlti-Dimensional Spline-Based Estimator (MUSE) for motion estimation: algorithm development and initial results.

Image registration and motion estimation play central roles in many fields, including RADAR, SONAR, light microscopy, and medical imaging. Because of its central significance, estimator accuracy, precision, and computational cost are of critical importance. We have previously presented a highly accurate, spline-based time delay estimator that directly determines sub-sample time delay estimates from sampled data. The algorithm uses cubic splines to produce a continuous representation of a reference signal and then computes an analytical matching function between this reference and a delayed signal. The location of the minima of this function yields estimates of the time delay. In this paper we describe the MUlti-dimensional Spline-based Estimator (MUSE) that allows accurate and precise estimation of multi-dimensional displacements/strain components from multi-dimensional data sets. We describe the mathematical formulation for two- and three-dimensional motion/strain estimation and present simulation results to assess the intrinsic bias and standard deviation of this algorithm and compare it to currently available multi-dimensional estimators. In 1000 noise-free simulations of ultrasound data we found that 2D MUSE exhibits maximum bias of 2.6 x 10(-4) samples in range and 2.2 x 10(-3) samples in azimuth (corresponding to 4.8 and 297 nm, respectively). The maximum simulated standard deviation of estimates in both dimensions was comparable at roughly 2.8 x 10(-3) samples (corresponding to 54 nm axially and 378 nm laterally). These results are between two and three orders of magnitude better than currently used 2D tracking methods. Simulation of performance in 3D yielded similar results to those observed in 2D. We also present experimental results obtained using 2D MUSE on data acquired by an Ultrasonix Sonix RP imaging system with an L14-5/38 linear array transducer operating at 6.6 MHz. While our validation of the algorithm was performed using ultrasound data, MUSE is broadly applicable across imaging applications.

Experimental system prototype of a portable, low-cost, C-scan ultrasound imaging device.

A system prototype of a future compact, low-cost medical ultrasound device is described and presented with experimental results. The prototype system consists of a 32 x 32 element, fully sampled 2-D transducer array and a printed circuit board (PCB) containing 16 custom "front-end" receive channel integrated circuits (ICs) with analog multiplexing and programmable logic. A PC that included a commercially available data acquisition card is used for data collection and analysis. Beamforming is performed offline using the direct sampled in-phase/quadrature (DSIQ) algorithm. Pulse-echo images obtained with the prototype are presented. Results from this prototype support the feasibility of a low-cost, pocket-sized, C-scan imaging device.

A spline-based approach for computing spatial impulse responses.

Computer simulations are an essential tool for the design of phased-array ultrasonic imaging systems. FIELD II, which determines the two-way temporal response of a transducer at a point in space, is the current de facto standard for ultrasound simulation tools. However, the need often arises to obtain two-way spatial responses at a single point in time, a set of dimensions for which FIELD II is not well optimized. This paper describes an analytical approach for computing the two-way, far-field, spatial impulse response from rectangular transducer elements under arbitrary excitation. The described approach determines the response as the sum of polynomial functions, making computational implementation quite straightforward. The proposed algorithm, named DELFI, was implemented as a C routine under Matlab and results were compared to those obtained under similar conditions from the well-established FIELD II program. Under the specific conditions tested here, the proposed algorithm was approximately 142 times faster than FIELD II for computing spatial sensitivity functions with similar amounts of error. For temporal sensitivity functions with similar amounts of error, the proposed algorithm was about 1.7 times slower than FIELD II using rectangular elements and 19.2 times faster than FIELD II using triangular elements. DELFI is shown to be an attractive complement to FIELD II, especially when spatial responses are needed at a specific point in time.