This PDF file contains the front matter associated with SPIE Proceedings Volume 6513, including the Title Page, Copyright information, Table of Contents, and Conference Committee listing.

We present a total-variation (TV)-based method for obtaining accurate image reconstruction in diffraction tomography (DT) from sparse data. Using computer-simulated data, we show that the TV-based method is effective in reconstructing accurate images using a total number of data samples comparable to or less than that of other current algorithms, such as filtered backpropagation or inverse scattering. Our algorithm is robust to the effects of measurement noise, and performs very well in limited angle scans. Overall our results indicate that TV minimization can be applied to DT image reconstruction under a variety of scan configurations and data conditions.

Aperture weighting functions are critical design parameters in the development of ultrasound systems because beam characteristics determine the contrast and point resolution of the final image. In previous work by our group, we developed a general apodization design method that optimizes a broadband imaging system's contrast resolution performance [1, 2]. In that algorithm we used constrained least squares (CLS) techniques and a linear algebra formulation of the system point spread function (PSF) as a function of the scalar aperture weights. In this work we replace the receive aperture weights with individual channel finite impulse response (FIR) filters to produce PSFs with narrower mainlobe widths and lower sidelobe levels compared to PSFs produced with conventional apodization functions. Our approach minimizes the energy of the PSF outside a defined boundary while imposing a quadratic constraint on the energy of the PSF inside the boundary. 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 results that 7-tap FIR filters can reduce sidelobe and grating lobe energy by 30dB and improve cystic contrast [3] by as much as 20dB compared to conventional apodization profiles. We also show experimental results where multi-tap FIR filters decrease sidelobe energy in the resulting 2D PSF and maintain a narrow mainlobe. Our algorithm has the potential to significantly improve ultrasound beamforming in any application where the system response is well characterized. Furthermore, this algorithm can be used to increase contrast and resolution in novel receive only beamforming systems [4, 5].

We consider the problem of imaging in a region where ultrasonic waves are multiply scattered. A transducer emits ultrasonic pulses in tissue where they scatter from a heterogeneity (e.g. a tumor) in the region of interest (ROI). The reflected signals are recorded and used to produce an image of tissue. Many of the conventional imaging methods assume the wave has scattered just once (Born-approximation) from the heterogeneity before returning to the sensor to be recorded. In reality, waves can scatter several times before returning to the detector. The purpose of this paper is to show how this restriction (the Born approximation or weak, single-scattering approximation) can be partially removed by incorporating a-priori known environmental scatterers, such as a cavity wall or bones into the background velocity model in the context of acoustic medical imaging. We also show how the partial removal of the Born approximation assumption leads to an enhanced angular resolution of heterogeneities that are present. We will illustrate our method using a locally planar scatterer, which is one of the simplest possible environments for the scatterer.

Ultrasonic reflection imaging has the potential to produce higher image resolution than transmission tomography, but imaging resolution and quality still need to be further improved for early cancer detection and diagnosis. We present an ultrasound reflection image reconstruction method using the split-step Fourier propagator. It is based on recursive inward continuation of ultrasonic wavefields in the frequency-space and frequency-wavenumber domains. The inward continuation within each extrapolation interval consists of two steps. In the first step, a phase-shift term is applied to the data in the frequency-wavenumber domain for propagation in a reference medium. The second step consists of applying another phase-shift term to data in the frequency-space domain to approximately compensate for ultrasonic scattering effects of heterogeneities within the breast. We use synthetic ultrasound pulse-echo data recorded around a ring for heterogeneous, computer-generated, numerical breast phantoms to study the imaging capability of the method. The phantoms are derived from an experimental breast phantom and a sound-speed tomography image of an in-vivo ultrasound breast data collected using a ring array. The heterogeneous sound-speed models used for pulse-echo imaging are obtained using a computationally effcient, first-arrival-time (time-of-flight) transmission tomography method. Our studies demonstrate that reflection image reconstruction using the split-step Fourier propagator with heterogeneous sound-speed models significantly improves image quality and resolution. We also numerically verify the spatial sampling criterion of wavefields for a ring transducer array.

Sound-speed tomography images can be used for cancer detection and diagnosis. Tumors have generally higher sound speeds than the surrounding tissue. Quality and resolution of tomography images are primarily determined by the insonification/illumination aperture of ultrasound and the capability of the tomography method for accurately handling heterogeneous nature of the breast. We investigate the capability of an efficient time-of-flight tomography method using transmission ultrasound from a ring array for reconstructing sound-speed images of the breast. The method uses first-arrival times of transmitted ultrasonic signals emerging from non-beamforming ultrasound transducers located around a ring. It properly accounts for ray bending within the breast by solving the eikonal equation using a finite-difference scheme. We test and validate the time-of-flight transmission tomography method using synthetic data for numerical breast phantoms containing various objects. In our simulation, the objects are immersed in water within a ring array. Two-dimensional synthetic data are generated using a finite-difference scheme to solve acoustic-wave equation in heterogeneous media. We study the reconstruction accuracy of the tomography method for objects with different sizes and shapes as well as different perturbations from the surrounding medium. In addition, we also address some specific data processing issues related to the tomography. Our tomography results demonstrate that the first-arrival transmission tomography method can accurately reconstruct objects larger than approximately five wavelengths of the incident ultrasound using a ring array.

High-resolution ultrasound imaging of the anterior portion of the eye has been shown to provide important information for sizing of intraocular lens implants, diagnosis of pathological conditions, and creation of detailed maps of corneal topography to guide refractive surgery. Current ultrasound imaging systems rely on mechanical scanning of a single acoustic element over the surface of the eye to create the three-dimensional information needed by clinicians. This mechanical scanning process is time-consuming and subject to errors caused by eye movement during the scanning period. This paper describes development of linear ultrasound imaging arrays intended to increase the speed of image acquisition and reduce problems associated with ocular motion. The arrays consist of a linear arrangement of high-frequency transducer elements designed to operate in the 50 - 75 MHz frequency range. The arrays are produced using single-crystal lithium niobate piezoelectric material, thin film electrodes, and epoxy-based acoustic layers. The array elements have been used to image steel test structures and bovine cornea.

Z-fiducial phantoms allow 3D ultrasound probe calibration with a single B-scan. One of the main difficulties in using this phantom is the need for reliable segmentation of the wires in the ultrasound images, which necessitates manual intervention. In this paper, we have shown how we can solve this problem by mounting a thin rubber membrane on top of the phantom. The membrane is segmented automatically and the wires can be easily located as they are at known positions relative to the membrane. This enables us to segment the wires automatically at the full PAL frame rate of 25Hz, to produce calibrations in real-time, while achieving accuracies similar to those reported in the literature. It takes approximately two minutes to set up the experiment-submerge the phantom in the water bath and locate the phantom in space with a pointer. After this, spatial calibration can be performed in real-time at 25 calibrations per second.

This paper further investigates the use of coded excitation for blood flow estimation in medical ultrasound. Traditional autocorrelation estimators use narrow-band excitation signals to provide sufficient signal-to-noise-ratio (SNR) and velocity estimation performance. In this paper, broadband coded signals are used to increase SNR, followed by sub-band processing. The received broadband signal, is filtered using a set of narrow-band filters. Estimating the velocity in each of the bands and averaging the results yields better performance compared to what would be possible when transmitting a narrow-band pulse directly. Also, the spatial resolution of the narrow-band pulse would be too poor for brightness-mode (B-mode) imaging and additional transmissions would be required to update the B-mode image. In the described approach, there is no need for additional transmissions, because the excitation signal is broadband and has good spatial resolution after pulse compression. Two different coding schemes are used in this paper, Barker codes and Golay codes. The performance of the codes for velocity estimation is compared to a conventional approach transmitting a narrow-band pulse. The study was carried out using an experimental ultrasound scanner and a commercial linear array 7 MHz transducer. A circulating flow rig was scanned with a beam-to-flow angle of 60°. The flow in the rig was laminar and had a parabolic flow-profile with a peak velocity of 0.09 m/s. The mean relative standard deviation of the reference method using an eight cycle excitation pulse at 7 MHz was 0.544% compared to the peak velocity in the rig. Two Barker codes were tested with a length of 5 and 13 bits, respectively. The corresponding mean relative standard deviations were 0.367% and 0.310%, respectively. For the Golay coded experiment, two 8 bit codes were used, and the mean relative standard deviation was 0.335%.

The majority of the commercial ultrasound scanners feature blood flow velocity estimation based on the autocorrelation method, yielding estimates of the axial velocity component only. For studying complex flow patterns like arterial bifurcations or venous confluences, 2-D vector velocity estimates would be needed. Synthetic aperture vector flow imaging could potentially provide this. The purpose of this paper is to test the synthetic aperture vector flow imaging method on challenging in-vivo data. Two synthetic aperture in-vivo data sets are acquired using a commercial linear array transducer and our RASMUS experimental ultrasound scanner. The first data set covers the femoral artery and the confluence of the femoral and saphenous vein of a healthy 26-year-old male volunteer. The second shows the carotid bifurcation of a healthy 32-year-old male volunteer. Both 2 second long data sets are processed, and movies of full vector flow images are generated. This paper presents still frames from different time instances of these movies. The movie from the femoral data tracks the accelerating velocity in the femoral artery during systole and a backwards flow at the end of the systole. A complex flow pattern is seen at the junction of the femoral and saphenous vein. The movie of the carotid bifurcation shows high velocities close to the separating wall between the internal and external carotid, and a vortex tendency at the outermost wall. The volume flow through the femoral artery is extracted from the velocity estimates of the femoral data set by assuming the artery is rotational symmetric. An average volume flow just above 500 ml/min was found for the 26-year-old volunteer. This is in agreement with values found in literature.

A new imaging technique has been developed for observing both strength and phase of pulsatile tissue-motion in a movie of brightness-mode ultrasonogram. The pulsatile tissue-motion is determined by evaluating the heartbeat-frequency component in Fourier transform of a series of pixel value as a function of time at each pixel in a movie of ultrasonogram (640x480pixels/frame, 8bit/pixel, 33ms/frame) taken by a conventional ultrasonograph apparatus (ATL HDI5000). In order to visualize both the strength and the phase of the pulsatile tissue-motion, we propose a pulsatile-phase image that is obtained by superimposition of color gradation proportional to the motion phase on the original ultrasonogram only at which the motion strength exceeds a proper threshold. The pulsatile-phase image obtained from a cranial ultrasonogram of normal neonate clearly reveals that the motion region gives good agreement with the anatomical shape and position of the middle cerebral artery and the corpus callosum. The motion phase is fluctuated with the shape of arteries revealing local obstruction of blood flow. The pulsatile-phase images in the neonates with asphyxia at birth reveal decreases of the motion region and increases of the phase fluctuation due to the weakness and local disturbance of blood flow, which is useful for pediatric diagnosis.

Doppler ultrasound velocity measurements are commonly used to diagnose atherosclerotic carotid artery disease. However, current Doppler techniques exhibit limitations with respect to sensitivity and specificity. We believe that advanced spectral analysis - including quantification of turbulence - could increase the diagnostic accuracy of duplex Doppler ultrasound. Routine application of advanced spectral analysis requires a practical technique to acquire and analyze the Doppler signal, which is compatible with clinical ultrasound machines. We describe the implementation of a technique for offline Doppler waveform analysis of carotid artery blood flow, using a portable MP3 recorder and custom analysis software. Forward and reverse audio signals were recorded with compression at 128 bps at prescribed points throughout the carotid bifurcation of human volunteers. Each data set was digitized at 44.1kHz and analyzed to produce velocity spectra at 12 ms intervals. From these instantaneous spectra, advanced Doppler indices of mean velocity and Fourier-based turbulence intensity (TI) were calculated. We found that MP3 compression had a negligible effect on the calculation of mean velocity data (0.17%) and TI (0.5%). We also found that Fourier-based TI was comparable to TI calculated by ensemble average. Finally, we were successful in applying this technique in vivo and demonstrated that long acquisitions and repeated measurements were possible in human volunteers. Our study demonstrates that it is feasible to acquire Doppler audio data using an MP3 recording device for off-line analysis, while only adding a short time to a conventional carotid exam.

A number of novel imaging modalities have been developed to interrogate the mechanical properties of tissue. A subset of these methods utilize acoustic radiation force to mechanically excite tissue and form images from the local responses of tissue to these excitations. These methods are attractive because of the ability to focus and steer the excitatory beams and to control their spatial and temporal characteristics using techniques similar to those employed in conventional ultrasonic imaging. These capabilities allow for a wide variety of imaging methods whose features are only beginning to be explored. However, radiation force based methods also present significant challenges. Tissue and transducer heating limit the tissue displacements achievable with radiation force applications and restrict image frame rates and fields-of-view. The small tissue displacements are difficult to detect and may be obscured by physiologic tissue motion. We review the fundamental limits of imaging methods based on radiation force generated by patient safety concerns and the impact of these limits on achievable image signal-to-noise ratios and frame rates. We also review our progress to date in the development and clinical evaluation of one class of radiation force imaging methods employing very brief impulses of radiation force.

Fundamental mechanical properties of tissue are altered by many diseases. Regional and systemic diseases can cause changes in tissue properties. Liver stiffness is caused by cirrhosis and fibrosis. Vascular wall stiffness and tone are altered by smoking, diabetes and other diseases. Measurement of tissue mechanical properties has historically been done with palpation. However palpation is subjective, relative, and not quantitative or reproducible. Elastography in which strain is measured due to stress application gives a qualitative estimate of Young's modulus at low frequency. We have developed a method that takes advantage of the fact that the wave equation is local and shear wave propagation depends only on storage and loss moduli in addition to density, which does not vary much in soft tissues. Our method is called shearwave dispersion ultrasonic velocity measurement (SDUV). The method uses ultrasonic radiation force to produce repeated motion in tissue that induces shear waves to propagate. The shear wave propagation speed is measured with pulse echo ultrasound as a function of frequency of the shear wave. The resulting velocity dispersion curve is fit with a Voight model to determine the elastic and viscous moduli of the tissue. Results indicate accurate and precise measurements are possible using this "noninvasive biopsy" method. Measurements in beef along and across the fibers are consistent with the literature values.

Several methods have been introduced in the past few years to quantify left-ventricular strain in order to detect myocardial ischemia and infarction. Myocardial Elastography is one of these methods, which is based on ultrasound Radio-Frequency (RF) signal processing at high frame rates for the highest precision and resolution of strain estimation. Myocardial elastography estimates displacement and strain during the natural contraction of the myocardium using cross-correlation techniques. We have previously shown that imaging of the myocardial strain at high precision allows the correct assessment of the contractility of the cardiac muscle and thus measurement of the extent of ischemia or infarct. In this paper, for the first time in echocardiography, we show how angle-independent techniques can be used to estimate and image the mechanics of normal and pathological myocardia, both in simulations and in vivo. First, the fundamental limits of 2D normal and principal strain component estimation are determined using an ultrasound image formation model and a 2D short-axis view of a 3D left-ventricular, finite-element model, in normal and ischemic configurations. Two-dimensional (i.e., lateral and axial) cumulative displacement and strain components were iteratively estimated and imaged using 1D cross-correlation and recorrelation techniques in a 2D search. Validation of these elastographic findings in one normal human subject was performed. Principal strains were also imaged for the characterization of normal myocardium. In conclusion, the feasibility of angle-independent, 2D myocardial elastography technique was shown through the calculation of the in-plane principal strains, which was proven essential in the reliable depiction of strains independent of the beam-tissue angle or the type of sonographic view used.

A novel ultrasonic elasticity imaging technique is being developed to study structural properties of hydropolymers including biological tissues. Radiation force is applied to harmonically stress the medium while ultrasonic Doppler and optical methods track deformation. This paper delineates basic system design and describes methods for pressure-field calibration using an acoustic radiometer, this extends to applying a radiation force to the media to remotely exert a locally oscillating stress field at the desired frequency within or on the medium surface. We use a single-element, spherically-focused, circular piston element driven by a pulsing voltage to produce a vibrating stress. Spectral Doppler techniques were successfully adapted to image the locally induced vibration. Our system delivers acoustic energy locally with an intensity matched to the acoustic attenuation and stiffness of the common biopolymers matrigel and chitosan.

This paper describes a new ultrasound elastography technique, power strain imaging, based on vibro-elastography (VE) techniques. With this method, tissue is compressed by a vibrating actuator driven by low-pass or band-pass filtered white noise, typically in the 0-20 Hz range. Tissue displacements at different spatial locations are estimated by correlation-based approaches on the raw ultrasound radio frequency signals and recorded in time sequences. The power spectra of these time sequences are computed by Fourier spectral analysis techniques. As the average of the power spectrum is proportional to the squared amplitude of the tissue motion, the square root of the average power over the range of excitation frequencies is used as a measure of the tissue displacement. Then tissue strain is determined by the least squares estimation of the gradient of the displacement field. The computation of the power spectra of the time sequences can be implemented efficiently by using Welch's periodogram method with moving windows or with accumulative windows with a forgetting factor. Compared to the transfer function estimation originally used in VE, the computation of cross spectral densities is not needed, which saves both the memory and computational times. Phantom experiments demonstrate that the proposed method produces stable and operator-independent strain images with high signal-to-noise ratio in real time. This approach has been also tested on a few patient data of the prostate region, and the results are encouraging.

Ultrasound elastography can provide tissue stiffness information that is complementary to the anatomy and blood flow information offered by conventional ultrasound machines, but it is computationally challenging due to many time-consuming modules and a large amount of data. To facilitate real-time implementations of ultrasound elastography, we have developed new methods that can significantly reduce the computational burden of common processing components in ultrasound elastography, such as the crosscorrelation analysis and spatial filtering applied to displacement and strain estimates. Using the new correlation-based search algorithm, the computational requirement of correlation-based search does not increase with the correlation window size. For typical parameters used in ultrasound elastography, the computation in correlation-based search can be reduced by a factor of more than 30. Median filtering is often performed to suppress the spike-like noise that results from correlation-based search. For fast median filtering, we have developed a method that efficiently finds a new median value utilizing the sort result of the previous pixel. With careful mapping of the new algorithms on digital signal processors, our work has led to development of a clinical ultrasound machine supporting real-time elastography. Our methods can help real-time implementations of various applications including ultrasound elastography, which could lead to increased use of ultrasound elastography in the clinic.

Ultrasound elastography measures the elastic properties of soft tissues using ultrasound signals. The elastic problem can be analyzed with tensor signal processing. In this work, we propose a new interpretation of elastography through the deformation tensor and its decomposition into both the strain and vorticity tensors. Vorticity gives information about the rotation of the inclusions that might help in the discrimination between malign and benign tumors without using biopsy. Although clinical validation is needed, synthetic experiments present reliable results.

This paper assesses lesion contrast and detection using sonoelastographic shear velocity imaging. Shear wave interference patterns, termed crawling waves, for a two phase medium were simulated assuming plane wave conditions. Shear velocity estimates were computed using a spatial autocorrelation algorithm that operates in the direction of shear wave propagation for a given kernel size. Contrast was determined by analyzing shear velocity estimate transition between mediums. Experimental results were obtained using heterogeneous phantoms with spherical inclusions (5 or 10 mm in diameter) characterized by elevated shear velocities. Two vibration sources were applied to opposing phantom edges and scanned (orthogonal to shear wave propagation) with an ultrasound scanner equipped for sonoelastography. Demodulated data was saved and transferred to an external computer for processing shear velocity images. Simulation results demonstrate shear velocity transition between contrasting mediums is governed by both estimator kernel size and source vibration frequency. Experimental results from phantoms further indicates that decreasing estimator kernel size produces corresponding decrease in shear velocity estimate transition between background and inclusion material albeit with an increase in estimator noise. Overall, results demonstrate the ability to generate high contrast shear velocity images using sonoelastographic techniques and detect millimeter-sized lesions.

Accurate and fast seed localization plays a key role in computing dosimetry for prostate brachytherapy. Because transrectal ultrasound is the primary imaging modality providing the guidance for prostate brachytherapy, an ultrasound-only approach for dosimetry would offer many benefits. In this paper, we propose an ultrasound only dosimetry solution, in which the brachytherapy seeds are located in reflected power images computed from ultrasonic radio frequency signals and the boundary of the prostate is delineated from B-mode TRUS and vibroelastography images as the prostate is stiffer than the surrounding tissue. The location of the implanted seeds relative to the prostate boundary is thus obtained. As only one imaging modality, ultrasound, is used, image registration is easy to implement. A prostate phantom with seeds embedded within it was built to evaluate the proposed approach. To measure the seed localization accuracy in the reflected power images, the phantom was scanned by CT as well. Experimental results show that the implanted seeds can be successfully located in the reflected power images with high contrast and accuracy, and that the contour of the "prostate" can be detected in the ultrasound vibro-elastography images outside the shadow of the seeds.

Plaque characterization through backscattered intravascular ultrasound (IVUS) signal analysis has been the subject of extensive study for the past several years. A number of algorithms to analyze IVUS images and underlying RF signals to delineate the composition of atherosclerotic plaque have been reported. In this paper, we present several realistic challenges one faces throughout the process of developing such algorithms to characterize tissue type. The basic tenet of ultrasound tissue characterization is that different tissue types imprint their own "signature" on the backscattered echo returning to the transducer. Tissue characterization is possible to the extent that these echo signals can be received, the signatures read, and uniquely attributed to a tissue type. The principal difficulty in doing tissue characterization is that backscattered RF signals originating as echoes from different groups of cells of the same tissue type exhibit no obvious commonality in appearance in the time domain. This happens even in carefully controlled laboratory experiments. We describe the method of acquisition and digitization of ultrasound radiofrequency (RF) signals from left anterior descending and left circumflex coronary arteries. The challenge of obtaining corresponding histology images to match to specific regions-of-interest on the images is discussed. A tissue characterization technique based on seven features is compared to a full spectrum based approach. The same RF and histology data sets were used to evaluate the performances of these two techniques.

We present the results of an animal tissue characterization study to demonstrate the effectiveness of a novel approach in collecting and analyzing ultrasound echo signals. In this approach, we continuously record RF echo signals backscattered from a tissue sample, while the imaging probe and the tissue are fixed in position. The continuously recorded RF data generates a time series of RF signal samples. The Higuchi fractal dimension of the resulting time series at each spatial coordinate of the RF frame, averaged over a region of interest, serves as our tissue characterizing feature. The proposed feature is used along with Bayesian classifiers and feed-forward neural networks to distinguish different types of animal tissue. Pairwise classification of four different types of animal tissue are performed. Accuracies are in the range of 68%-96% and are significantly higher than the natural split of the data. The promising results of this study show that analysis of RF time series as proposed here, can potentially give rise to effective measures for ultrasound-based tissue characterization.

In the projection geometry, the detected ultrasound energy through a soft-tissue is mainly attributed to the attenuated primary intensity and the scatter intensity. In order to extract ultrasound image of attenuated primary beam out of the detected raw data, the scatter component must be carefully quantified for restoring the original image. In this study, we have designed a set of apparatus to modeling the ultrasound scattering in soft-tissue. The employed ultrasound imaging device was a C-Scan (projection) prototype using a 4th generation PE-CMOS sensor array (model I400, by Imperium Inc., Silver Spring, MD) as the detector. Right after the plane wave ultrasound transmitting through a soft-tissue mimicking material (Zerdine, by CIRS Inc., Norfolk, VA), a ring aperture is used to collimate the signal before reaching the acoustic lens and the PE-CMOS sensor. Three sets of collimated ring images were acquired and analyzed to obtain the scattering components as a function of the off-center distance. Several pathological specimens and breast phantoms consisting of simulated breast tissue with masses, cysts and microcalcifications were imaged by the same C-Scan imaging prototype. The restoration of these ultrasound images were performed by using a standard deconvolution computation. Our study indicated that the resultant images show shaper edges and detailed features as compared to their unprocessed counterparts.

Optoacoustic imaging, a novel noninvasive modality, combines the advantages of optical methods and the ultrasound technique. The optoacoustic technique is based on tissue irradiation with nanosecond laser pulses and detection of ultrasound waves generated due to thermo-elastic expansion. Using a modified Monte Carlo technique and solution of wave equation for velocity potential, we modeled optoacoustic signals from cylindrical blood vessels with varying oxygenation and varying total hemoglobin concentration. A specially designed computer code was used for reconstruction of images of absorbed energy in the blood vessels and surrounding tissues. Then we performed a set of experiments with our optoacoustic system and phantoms that simulate blood vessels such as veins and arteries at depths of up to 2 cm. The optoacoustic signals from the phantoms were used for reconstruction of 2-D cross-section images and correlated well with geometry and optical properties of the phantoms. The obtained data suggest that the developed optoacoustic imaging approach can be used for accurate mapping of blood oxygenation and hemoglobin concentration in blood vessels.

Conventional methods for mapping cardiac current fields have either poor spatial resolution (e.g. ECG) or are time consuming (e.g., intra-cardiac catheter electrode mapping). We present a method based on the acousto-electric effect (AEE) and lead field theory for minimally-invasive mapping of 2D current distributions. The AEE is a pressure-induced conductivity modulation in which focused ultrasound can be used as a spatially-localized pressure source. As a proof of principle we generated a 2D dipole field in a thin bath of 0.9% NaCl solution by injecting 28 mA through a pair of electrodes. A 7.5 MHz transducer was focused on the bath from below. A recording electrode was rotated along the boundary of the bath in 20° steps. For each angle, the transducer was swept over the bath in a raster scan. A pulse-echo and an AEE voltage trace were acquired at each point. The AEE traces were combined in post-processing as if coming from a multi-electrode circular array. The direction and magnitude of the current field at each point in the plane was estimated from the AEE and compared to simulation. The potential field was independently mapped using a roving monopolar electrode. The correlation coefficient between this map and the simulated field was 0.9957. A current source density analysis located the current source and sink to within 1±2 mm of their true position. This method can be extended to 3 dimensions and has potential for use in rapid mapping of current fields in the heart with high spatial resolution.

Generation of tissue harmonic signals during acoustic propagation is based on the combined effect of two different spectral interactions of the transmit signal. One produces harmonic whose frequency is the sum of transmit frequencies. The other results in harmonic at difference frequency of the transmit signals. Both the frequency-sum component and the frequency-difference component are sensitive to the phase of their constitutive spectral signals. When the two components are in-phase, enhancement of the native harmonic signal is feasible. Otherwise, they may cancel out each other and result in weak harmonic amplitude. For the frequency-sum component, its phase is solely related to the fundamental signal in the transmit waveform. On the other hand, the phase of the frequency-difference component is determined by the phase difference between the third harmonic signal and the fundamental signal. Results indicate that the relative phasing between the frequency-sum component and the frequency-difference component significantly changes the amplitude of the second harmonic signal. By simultaneously transmitting both fundamental signal and third harmonic signal with proper phases such that the frequency-difference component is in-phase with the frequency-sum component, the amplitude of second harmonic signal can be increased while the lateral harmonic beam pattern remains unchanged as compared to conventional situations. The second harmonic signal could be also reduced significantly when the two components are out of phase. Hence, third harmonic transmit phasing has potential for improving signal-to- noise ratio in tissue harmonic imaging or for enhancing image contrast in contrast agent imaging by suppression of tissue harmonics.

Image registration, or equivalently motion estimation, plays a central role in a broad range of ultrasound applications including elastography, estimation of blood or tissue motion, radiation force imaging, and extended field of view imaging. Because of its central significance, motion estimation accuracy, precision, and computational cost are of critical importance. Furthermore, since motion estimation is typically performed on sampled signals, while estimates are usually desired over a continuous domain, performance should be considered in conjunction with associated interpolation. 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 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 describe a MUlti-dimensional Spline-based Estimator (MUSE) that allows accurate and precise estimation of multi-dimensional displacements/strain components from multi-dimensional data sets. In this paper we describe the mathematical formulation for three-dimensional (3D) 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 1,000 noise-free simulations we found that 2D MUSE exhibits maximum bias errors of 4.8nm and 297nm in range and azimuth respectively. The maximum simulated standard deviation of estimates in both dimensions was comparable at 0.0026 samples (corresponding to 54nm axially and 378nm laterally). These results are two to three orders of magnitude lower than currently used 2D tracking methods. Simulation of performance in 3D yielded similar results to those observed in 2D. We also performed experiments using 2D MUSE on an Ultrasonix Sonix RP imaging system with an L14-5/38 linear array transducer operating at 6.6MHz. With this experimental data we found that bias errors were significantly smaller than geometric errors induced by machining of the transducer mount.

The quantitative assessment of and compensation for catheter rotation in Intravascular Ultrasound (IVUS) images presents a fundamental problem for noninvasive characterization of the mechanical properties of the coronary arteries. A method based on the scale-space optical flow algorithm with a feature-based weighting scheme is proposed to account for the aforementioned artifact. The computed vector field, describing the transformation between two consecutive frames, allows the quantitative assessment of the amount of vessel wall tissue motion, which is directly related to the catheter rotation. Algorithm accuracy and robustness were demonstrated on a tissue-mimicking phantom, subjected to controlled amount of angular deviation. The proposed method shows a great reliability in prediction of catheter rotational motion up to 4°.

Epidural anesthesia can be a difficult procedure, especially for inexperienced physicians. The use of ultrasound imaging can help by depicting the location of the epidural space to choose the needle trajectory appropriately. Anatomical features in the lower back are not always clearly visible because of speckle poor reflection from structures at certain angles, and shadows from bony surfaces. Spatial compounding has the potential to reduce speckle and emphasize structures by averaging a number of images taken at different isonation angles. However, the beam-steered images are not perfectly aligned due to non-constant speed of sound causing refraction errors. This means compounding can blur features. A non-rigid registration method, called warping, shifts each block of pixels of the beam-steered images in order to find the best alignment to the reference image without beam-steering. By applying warping, the features become sharper after compounding. To emphasize features further, edge detection is also applied to the individual images in order to select the best features for compounding. The warping and edge detection parameters are calculated in real-time for each acquired image. In order to reduce computational complexity, linear prediction of the warping vectors is used. The algorithm is tested on a phantom of the lower back with a linear probe. Qualitative comparisons are made among the original plus combinations of compounding, warping, edge detection and linear prediction. The linear gradient and Laplacian of a Gaussian are used to quantitatively assess the visibility of the bone boundaries and ligamentum flavum on the processed images. The results show a significant improvement in quality.

We present a new method to evaluate 4D (3D + time) cardiac ultrasound data sets by nonrigid spatio-temporal image registration. First, a frame-to-frame registration is performed that yields a dense deformation field. The deformation field is used to calculate local spatiotemporal properties of the myocardium, such as the velocity, strain and strain rate. The field is also used to propagate particular points and surfaces, representing e.g. the endo-cardial surface over the different frames. As such, the 4D path of these point is obtained, which can be used to calculate the velocity by which the wall moves and the evolution of the local surface area over time. The wall velocity is not angle-dependent as in classical Doppler imaging, since the 4D data allows calculating the true 3D motion. Similarly, all 3D myocardium strain components can be estimated. Combined they result in local surface area or volume changes which van be color-coded as a measure of local contractability. A diagnostic method that strongly benefits from this technique is cardiac motion and deformation analysis, which is an important aid to quantify the mechanical properties of the myocardium.

We introduce a new speckle suppression approach for 3-D ultrasound images. The proposed method seeks to enhance volume visualization of 3-D ultrasound images, and improve the accuracy of volume determination. Extended from 2-D nonlinear multiscale wavelet diffusion, the proposed method is developed on the basis of an integration of the 3-D nonlinear diffusion and 3-D dyadic wavelet transform techniques. Our approach uses the normalized wavelet modulus as an edge map to expose the intrinsic speckle/edge relation. Relying on the statistical analysis of this edge map, the method is able to classify homogenous speckle regions and edges in a 3-D volume, as well as provide strong speckle suppression and boundary preservation. Our method is validated using both synthetic and real 3-D ultrasonic images. Performance improvement over other filters is quantified by evaluating standard quality indices.

Ultrasound (US) is one of the most used imaging modalities today as it is cheap, reliable, safe and widely available. There are a number of issues with US images in general. Besides reflections which is the basis of ultrasonic imaging, other phenomena such as diffraction, refraction, attenuation, dispersion and scattering appear when ultrasound propagates through different tissues. The generated images are therefore corrupted by false boundaries, lack of signal for surface tangential to ultrasound propagation, large amount of noise giving rise to local properties, and anisotropic sampling space complicating image processing tasks. Although 3D Transrectal US (TRUS) probes are not yet widely available, within a few years they will likely be introduced in hospitals. Therefore, the improvement of automatic segmentation from 3D TRUS images, making the process independent of human factor is desirable. We introduce an algorithm for attenuation correction, reducing enhancement/shadowing effects and average attenuation effects in 3D US images, taking into account the physical properties of US. The parameters of acquisition such as logarithmic correction are unknown, therefore no additional information is available to restore the image. As the physical properties are related to the direction of each US ray, the 3D US data set is resampled into cylindrical coordinates using a fully automatic algorithm. Enhancement and shadowing effects, as well as average attenuation effects, are then removed with a rescaling process optimizing simultaneously in and perpendicular to the US ray direction. A set of tests using anisotropic diffusion are performed to illustrate the improvement in image quality, where well defined structures are visible. The evolution of both the entropy and the contrast show that our algorithm is a suitable pre-processing step for segmentation tasks.

Breast cancer mass screening is widely performed by mammography but in some population with dense breast, ultrasonography is much effective for cancer detection. For this purpose it is necessary to develop special ultrasonic equipment and the system for breast mass screening. It is important to design scanner, image recorder, viewer with CAD (Computer-assisted detection) as a system. Authors developed automatic scanner which scans unilateral breast within 30 seconds. An electric linear probe visualizes width of 6cm, the probe moves 3 paths for unilateral breast. Ultrasonic images are recorded as movie files. These files are treated by microcomputer as volume data. Doctors can diagnose by digital rapid viewing with 3D function. It is possible to show unilateral or bilateral images on a screen. The viewer contains reporting function as well. This system is considered enough capability to perform ultrasonic breast cancer mass screening.

Three-dimensional (3D) ultrasound has become a useful tool in cardiac imaging, OB/GYN and other clinical applications. It enables clinicians to visualize the acquired volume and/or planes that are not easily accessible using 2D ultrasound, in addition to providing an intuitive understanding of the structural anatomy in three dimensions. One effective way to examine the acquired volumetric data is by clipping away parts of the volume using cross-sectional cuts to reveal the underlying anatomy masked by other structures. Ideally, such boundaries should reflect the orientation and location of the clip surfaces without altering the information content of the original data. Because of the artificial surface introduced by the clip boundary, shading employed to enhance the surfaces of the object gets modified, resulting in inconsistent shading and noticeable artifacts in the case of ultrasound data. Consistent shading of clip surfaces was previously studied for graphics hardware-based volume rendering, and an algorithm was developed and demonstrated in MRI, CT and non-medical datasets. However, that algorithm cannot be applied directly to fast software-based rendering approaches such as the shear-warp algorithm. Furthermore, ultrasound data require a different clipping approach due to their fuzzy nature, lower signal-to-noise ratios, and real-time requirements. In this paper, we present a software-based volume clipping technique that can effectively and efficiently overcome the difficulties associated with the shading of the clip boundaries in ultrasound data using shear-warp. Our technique improves the viewer's comprehension of the clip boundary without altering the original information content within the volume. The method has been implemented on programmable processors while maintaining the interactive speed in rendering.

Active contours have been used in a wide variety of image processing applications due to their ability to effectively distinguish image boundaries with limited user input. In this paper, we consider 3D gradient vector field (GVF) active surfaces and their application in the determination of the volume of the mouse heart left ventricle. The accuracy and efficacy of a 3D active surface is strongly dependent upon the selection of several parameters, corresponding to the tension and rigidity of the active surface and the weight of the GVF. However, selection of these parameters is often subjective and iterative. We observe that the volume of the cardiac muscle is, to a good approximation, conserved through the cardiac cycle. Therefore, we propose using the degree of conservation of heart muscle volume as a metric for assessing optimality of a particular set of active surface parameters. A synthetic dataset consisting of nested ellipsoids of known volume was constructed. The outer ellipsoid contracted over time to imitate a heart cycle, and the inner ellipsoid compensated to maintain constant volume. The segmentation algorithm was also investigated in vivo using B-mode data sets obtained by scanning the hearts of three separate mice. Active surfaces were initialized using a broad range of values for each of the parameters under consideration. Conservation of volume was a useful predictor of the efficacy of the model for the range of values tested for the GVF weighting parameter, though it was less effective at predicting the efficacy of the active surface tension and rigidity parameters.

Three-dimensional, freehand ultrasound is an imaging technique that has seen increasing applications in computer assisted surgery. A key element of this technique is image calibration, in order to estimate a three-dimensional homogeneous transformation that maps the position of individual pixels from the ultrasound image coordinate to the ultrasound probe coordinate frames. The transformation is typically calculated through imaging a calibration phantom of known geometry, and solving for the transformation parameters (either in closed-form or iteratively). The calibration error achieved through this process is usually assumed to be constant for all the pixels in the image. In this paper, we propose a novel method to estimate the calibration accuracy for individual pixels within an ultrasound image by employing the Unscented Kalman Filter (UKF). Based on the variances of calibration parameters extracted by UKF, a mean square residual error is estimated for each individual pixel in the ultrasound image. We demonstrate that the calibration error could in fact significantly vary for different pixels in the image. This observation could potentially impact the image registration process in computer assisted surgery applications. The method has been validated through simulations and experiments.

We propose a two-step approach to segment closed surfaces in 3D of arbitrary topology. First, a pre segmentation step with an active contour method is performed. This evolution process does not take into account topology adaptions. Topologically correct segmentations are derived with Kazhdan's algorithm in a second step. Kazhdan's algorithm requires information on the surface normals, which are obtained from the active contour method. We show that the two-step algorithm is computationally efficient. Moreover, we apply the algorithms for segmentation of 3D ultrasound data.

The most intuitive way to perform freehand 3D ultrasound calibration is to locate fiducials in the scan plane directly with a pointer. The main problem of using this approach is the difficulty of aligning the tip of the pointer with the scan plane. The thick beam width makes the tip of the pointer visible in the B-scan even if the tip is not exactly in the elevational centre of the scan plane. Furthermore, reliable automatic segmentation of isolated points in ultrasonic imaging systems is difficult. As a result, it is usual to rely on manual segmentation, making calibration a lengthy process. In this paper, we present a novel phantom that solves the alignment problem and simplifies the segmentation process, while maintaining the other advantages of using a pointer.

Microcirculation volumetric flow rate is a significant index in diseases diagnosis and treatment such as diabetes and cancer. In this study, we propose an integrated algorithm to assess microcirculation volumetric flow rate including estimation of blood perfused area and corresponding flow velocity maps based on high frequency destruction/contrast replenishment imaging technique. The perfused area indicates the blood flow regions including capillaries, arterioles and venules. Due to the echo variance changes between ultrasonic contrast agents (UCAs) pre- and post-destruction two images, the perfused area can be estimated by the correlation-based approach. The flow velocity distribution within the perfused area can be estimated by refilling time-intensity curves (TICs) after UCAs destruction. Most studies introduced the rising exponential model proposed by Wei (1998) to fit the TICs. Nevertheless, we found the TICs profile has a great resemblance to sigmoid function in simulations and in vitro experiments results. Good fitting correlation reveals that sigmoid model was more close to actual fact in describing destruction/contrast replenishment phenomenon. We derived that the saddle point of sigmoid model is proportional to blood flow velocity. A strong linear relationship (R = 0.97) between the actual flow velocities (0.4-2.1 mm/s) and the estimated saddle constants was found in M-mode and B-mode flow phantom experiments. Potential applications of this technique include high-resolution volumetric flow rate assessment in small animal tumor and the evaluation of superficial vasculature in clinical studies.

It is difficult to automatically detect tumors and extract lesion boundaries in ultrasound images due to the variance in shape, the interference from speckle noise, and the low contrast between objects and background. The enhancement of ultrasonic image becomes a significant task before performing lesion classification, which was usually done with manual delineation of the tumor boundaries in the previous works. In this study, a linear support vector machine (SVM) based algorithm is proposed for ultrasound breast image training and classification. Then a disk expansion algorithm is applied for automatically detecting lesions boundary. A set of sub-images including smooth and irregular boundaries in tumor objects and those in speckle-noised background are trained by the SVM algorithm to produce an optimal classification function. Based on this classification model, each pixel within an ultrasound image is classified into either object or background oriented pixel. This enhanced binary image can highlight the object and suppress the speckle noise; and it can be regarded as degraded paint character (DPC) image containing closure noise, which is well known in perceptual organization of psychology. An effective scheme of removing closure noise using iterative disk expansion method has been successfully demonstrated in our previous works. The boundary detection of ultrasonic breast lesions can be further equivalent to the removal of speckle noise. By applying the disk expansion method to the binary image, we can obtain a significant radius-based image where the radius for each pixel represents the corresponding disk covering the specific object information. Finally, a signal transmission process is used for searching the complete breast lesion region and thus the desired lesion boundary can be effectively and automatically determined. Our algorithm can be performed iteratively until all desired objects are detected. Simulations and clinical images were introduced to evaluate the performance of our approach. Several types of cysts with different contours and contrast resolutions images were simulated with speckle characteristics. Four thousand sub-images of tumor objects and speckle-noised background were used for SVM training. Comparison with conventional algorithms such as active contouring, the proposed algorithm does not need to position any initial seed point within the lesion and is able to detect simultaneously multiple irregular shape lesions in a single image, thus it can be regarded as a fully automatic process. The results show that the mean normalized true positive area overlap between true contour and contour obtained by the proposed approach is 90%.

The elevational distance between two ultrasound images can be obtained from the correlation between the two images, leading to sensorless freehand 3D ultrasound systems. Most of these systems rely on the correlation between patches of fully developed speckles (FDS). Previous work has compared different FDS detectors and concluded that the elevational distance measurement limited to the FDS patches obtained by low order moment test yields significantly more accurate results than other FDS detectors. However, small coherent and FDS regions are spread throughout a typical ultrasound image of real tissue. This makes it extremely unlikely to find a regularly shaped (conventionally a rectangle) FDS patch, making it infeasible to estimate elevational distance accurately¹. In this work, first we propose a simple and fast algorithm which is capable of detecting arbitrarily irregular FDS regions in an ultrasound image. In vitro experiments on beef liver, beef steak and chicken breast indicates that the proposed algorithm generates remarkably more FDS patches than the current methods. Preliminary results show that the FDS patches obtained by this algorithm generate more accurate elevational distance measurement. Second, we propose a new calibration scheme to generate decorrelation curves. At a particular location in the image, conventional methods acquire one decorrelation curve. We create multiple curves, as a function of particular statistical properties of the patch. The results reveal a theoretically expected relation between the decorrelation curve and the statistical properties of the patch. As a result of this calibration based on the patch statistical properties, improvement in the out of plane motion estimation is expected.

Delay-and-sum array beamforming is an essential part of signal processing in ultrasound imaging. Although the principles are simple, there are many implementation details to consider for obtaining a reliable and computational efficient beamforming. Different methods for calculation of time-delays are used for different waveforms. Various inter-sample interpolation schemes such as FIR-filtering, polynomial, and spline interpolation can be chosen. Apodization can be any preferred window function of fixed size applied on the channel signals or it can be dynamic with an expanding and contracting aperture to obtain a preferred constant F-number. An effective and versatile software toolbox for off-line beamformation designed to address all of these issues has been developed. It is capable of exploiting parallelization of computations on a Linux cluster and is written in C++ with a MATLAB(MathWorks Inc.) interface. It is an aid to support simulations and experimental investigation of 3D imaging, synthetic aperture imaging, and directional flow estimation. A number of parameters are necessary to fully define the spatial beamforming and some parameters are optional. All spatial specifications are given in 3D space such as the physical positions of the transducer elements during transmit and receive and the positions of the points to beamform. The points of focus are defined as a collection of lines each having an origin, a direction, a distance between points and a length. The transducer, the points to beamform, and the apodization are defined as individual objects and a combination of these define the actual beamforming. Once the beamforming is defined, the time-delays and apodization values for every combination of transmit elements, receive elements and focus points can be calculated and stored in lookup-tables (LUT). Parametric beamforming can also be applied where calculations are done by demand, thus, reducing the storage demand dramatically. On a standard PC with a Pentium 4, 2.66 GHz processor running Linux the toolbox can beamform 100,000 points in lines of various directions in 20 seconds using a transducer of 128 elements, dynamic apodization and 3rd order polynomial interpolation. This is a decrease in computation time of at least a factor of 15 compared to an implementation directly in MATLAB of a similar beamformer.

Classic Doppler equation can only provide the axial velocity of blood flow. To acquire the complete flow vector, estimation of the non-axial flow velocity is essential. For Doppler-bandwidth-based transverse estimation, however, accuracy is limited because of the complex dependence of the Doppler bandwidth on the geometry and the location of the sample volume in the vessel. Specifically, the Doppler bandwidth tends to be overestimated because it is conventionally decided from the difference between maximum Doppler frequency and Doppler shift frequency. The maximum Doppler frequency only depends on the peak flow velocity within the vessel and can be used as a stable parameter in flow estimation. However, the Doppler shift frequency is susceptible to the position of the sample volume and it decreases when the sample volume is not centered within the vessel. The distance between the center of the sample volume and the central line of the vessel is referred to as the position offset of the sample volume. Based on the stable nature of maximum Doppler frequency, a novel method utilizing the differential maximum Doppler frequencies from two parallel beams with different beam widths is proposed to improve the accuracy of transverse estimation. In vitro experiments were performed to validate the proposed method and results were compared with the conventional method. In this study, a steady flow condition was considered and two 5-MHz pistons were used to generate the two beams with different widths. For the conventional method, it is demonstrated that the Doppler bandwidth is severely overestimated when the position offset is present. For the proposed method, however, the differential maximum Doppler frequency is relatively stable even in the presence of the position offset as long as the sample volume is sufficient in length. Hence, both accuracy and stability of the transverse estimation can be significantly improved by taking advantage of the differential maximum Doppler frequency.

The irradiation of the skin with low-frequency ultrasound (42 MHz) increases the skin permeability, allowing the US stimulated drug delivery (sonophoresis). The changes in the skin permeability is generally demonstrated with the measurement of corneometry and transepidermal water loss (TEWL). A novel ultrasound scanner with a 50 MHz probe was used for acquiring images of the skin (penetration depth few millimeters). The images show the different epidermal and dermis layers. A specially designed plexiglas basin containing an US transducer was used. Water was used as matching medium. The transducer was set to generate a 42 MHz continuous wave US beam with an intensity of 150 mW/cm² for a chosen preset time. Ninety healthy volunteers were submitted to exposure of the back of the hand. The back of the hand of each person was scanned at 50 MHz before the irradiation and after 1, 15 and 60 minutes. A significant variation of the stratum corneum and the derma on the sonographic image was found. A particular software code was developed in order to quantify the amount of the variation in the image, using different parameters (entropy, energy, skewness, kurtosis, etc.) related to the pixel value in different regions of interest and to the cumulated profile along lines perpendicular to the skin surface. The variations in the parameters so defined were demonstrated to be statistically significant and with a sensibility much higher than corneometry and TEWL. This new approach allow to better understand the mechanism and quantify the changes in the skin permeability.

The class of geometric deformable models, also known as level sets, has brought tremendous impact on medical imagery due to its capability of topology preservation and fast shape recovery. Ultrasound images are often characterized by a high level of speckle causing erroneous detection of contours. This work proposes a new stopping term for level sets, based on the coefficient of variation and a multilayer perceptron, in order to robustly detect the contours in ultrasound images. Successful applications of the MLP-Level Sets to detection of contours on synthetics and real images are presented.

Intravascular Ultrasound (IVUS) plays a significant role in diagnostics of atherosclerotic diseases. Simulation of imaging techniques promises a better understanding of the physical background and segmentation strategies. Most simulation approaches describe ultrasonic backscattering using wave-equation based simplifications. More complicated real-time simulation techniques are not available so far. In this paper, we present an empirical model derived from wave-equations given by the Rayleigh integration method. According to boundary conditions and weak scatterers, a hybrid approach including the Beer-Lambert law to model attenuation is introduced. Scatterers are described by a 4D vessel-system model based on elastic tubes. Sophisticated discretization and numerical simplifications in addition to a highly optimized implementation of the model yields a real-time and realistic IVUS simulation with 20 frames/s on a 3.2 GHz Pentium 4 PC.

The purpose of this research was to introduce and analyze a technique for enhancing elasticity image quality using locally adaptive Gaussian filtering. To assess the performance of this filtering method for reconstructing images with missing or degraded data, heterogeneous images were simulated with circular regions of intensity twice that of the surrounding material. Missing pixel data was introduced by thresholding a uniformly distributed noise matrix. Results demonstrate locally adaptive Gaussian filtering accurately reconstructs the original image while preserving boundary detail. To further analyze the performance of this filtering technique, multiple local image regions were suppressed and normally distributed noise superimposed. Consequently, locally adaptive Gaussian filtering is capable of reconstructing local missing data whereas both median and conventional Gaussian filtering fails. Using compressional elastographic experimental data, results illustrate that locally adaptive Gaussian filtering is capable of minimizing decorrelation noise artifacts while preserving lesion boundaries. Additionally, results obtained using vibrational shear velocity sonoelastography further illustrate the ability of locally adaptive Gaussian filtering to enhance image quality by minimizing estimator noise degradation in comparison to conventional spatial filtering techniques. Overall, results indicate the feasibility of employing this spatial filtering technique for improving elasticity image quality while preserving lesion boundaries.

In this paper, we propose a fully automatic system for analyzing ecographic movies of flow-mediated dilation. Our approach uses a spline-based active contour (deformable template) to follow artery boundaries during the FMD procedure. A number of preprocessing steps (grayscale conversion, contrast enhancing, sharpening) are used to improve the visual quality of frames coming from the echographic acquisition. Our system can be used in real-time environments due to the high speed of edge recognition which iteratively minimizes fitting errors on endothelium boundaries. We also implemented a fully functional GUI which permits to interactively follow the whole recognition process as well as to reshape the results. The system accuracy and reproducibility has been validated with extensive in vivo experiments.

High intensity focused ultrasound (abbreviated as HIFU) has its potential in tumor treatment due to its non-invasive benefits. During HIFU exposure, cavitation (generation of gas bubbles) is often observed, which can be an indication of potential lesion created by HIFU power. Due to a large difference in ultrasound acoustic properties between the gas bubble and surrounding tissues, ultrasonic energy is reflected and scattered at the HIFU focus, thus indicating activity around the focal area and often interfering HIFU dosage delivery. A good understanding and control of cavitation phenomenon could potentially enhance the HIFU delivery and treatment outcomes. Quantifying the onset timing and extent of the cavitation could be potentially used for detecting HIFU effects and therapy guidance. In this paper, we study the relationships among HIFU parameters, the characteristics of cavitation quantified from ultrasound imaging, and characteristics of the final tissue lesion created by HIFU. In our study, we used 12 freshly excised pig brains in vitro for observation and analysis of cavitation activities during HIFU exposure with different HIFU parameters. Final lesions were examined by slicing the brain tissues into thin slices and 3D volume was constructed with segmentation of the lesion. HIFU parameters, cavitation activities through image processing and lesion characterization were correlated. We also present our initial understanding of the process of cavitation activities under certain HIFU parameters and control of such activities that could lead to optimal lesion

Considering the coding-excitation technology applied in ultrasonic systems, pre-decoding by multi-center before beam-synthesis is recognized as the best method for decoding. Compared with the method of decoding after synthesizing, the former avoids the inferior quality of side-lobe performance invited by beam-synthesis (the attenuation is more than 15dB). However, it is restricted by its great requirement to hardware cost resources so that pre-decoding method couldn't be made the most of in practice. In order to resolve the practical issue, this paper advances a set of project to retrench hardware cost by optimizing the decoding algorithm in theory. The resulting data based on Golay code with Quartus II validates the validity and feasibility of this project.