This PDF file contains the front matter associated with SPIE Proceedings Volume 8320, including the Title Page, Copyright information, Table of Contents, and the Conference Committee listing.

Waveform tomography has the potential to quantitatively reconstruct the sound speed values of breast tumors. It is difficult to obtain quantitative values of the sound speed of breast tumors when their sizes are in the order of, or smaller than, the ultrasound wavelength. Because of the ill-posedness of the full-waveform inversion, regularization techniques are usually used to improve reconstruction. We develop an ultrasound waveform tomography method with the total-variation regularization to improve sound-speed reconstructions of small breast tumors. Our numerical examples demonstrate that our ultrasound waveform tomography with the total-variation regularization is a promising tool for quantitative estimation of the sound speed of small breast tumors.

Ultrasound waveform tomography takes wave propagation effects into account during image reconstruction, and has the potential to produce accurate estimates of the sound speeds of small breast tumors. However, waveform tomography is computationally time-consuming for large datasets acquired using a synthetic-aperture ultrasound tomography system that consists of hundreds to thousands of transducer elements. We introduce a source encoding approach to ultrasound waveform tomography to significantly improve the computational efficiency. The method simultaneously simulates ultrasound waveforms emitted from multiple transducer elements. To distinguish the effect of different sources, we apply a random phase to each source. The random phase helps eliminate the unwanted cross interferences produced by different sources. This approach greatly reduces the computational time of ultrasound waveform tomography to one tenth of that for the original waveform tomography, and makes it feasible for ultrasound waveform tomography in clinical applications.

Ultrasound Computer Tomography (UCT) is an imaging technique which has proved effective for soft-tissue (breast, liver,...) characterization. More recently, the use of UCT has been envisaged for bone imaging. In this field, the large variations of impedance distribution (high contrast) require that a finer model of wave propagation be integrated into the reconstruction scheme. Here, the tomographic procedure used is adapted to broadband data acquired in scattering configurations while the heterogeneous objects (Born approximation) are probed by spherical waves. An "elliptical" Fourier transform has been derived to solve the near-field inverse problem. This transform differs from the standard Fourier Transform in that, instead of plane waves, families of harmonic ellipsoidal waves are considered. For soft tissues it is possible to separate the impedance and speed of sound contributions and to reconstruct their cartographies using dedicated near-field Radon transforms. In the case of highly heterogeneous media such as bones, iterative inversion schemes are proposed. The various reconstruction procedures are set against experiments.

A promising candidate for improved imaging of breast cancer is ultrasound computer tomography (USCT). Current experimental USCT systems are still focused in elevation dimension resulting in a large slice thickness, limited depth of field, loss of out-of-plane reflections, and a large number of movement steps to acquire a stack of images. 3DUSCT emitting and receiving spherical wave fronts overcomes these limitations. We built an optimized 3DUSCT with nearly isotropic 3DPSF, realizing for the first time the full benefits of a 3Dsystem. In this paper results of the 3D point spread function measured with a dedicated phantom and images acquired with a clinical breast phantom are presented. The point spread function could be shown to be nearly isotropic in 3D, to have very low spatial variability and fit the predicted values. The contrast of the phantom images is very satisfactory in spite of imaging with a sparse aperture. The resolution and imaged details of the reflectivity reconstruction are comparable to a 3TeslaMRI volume of the breast phantom. Image quality and resolution is isotropic in all three dimensions, confirming the successful optimization experimentally.

Accurate time delay estimation is critical for a wide range of remote sensing applications. We propose a technique that exploits the redundancy between absolute and relative time delays in transducer arrays as a means to reduce the level of noise present in the measurements. We formalize the problem of interest and present two different strategies to solve it. The first strategy is optimal in the mean square sense but requires a quadratic programming solver. The second approach is based on a sub-optimal iterative denoising technique. The effectiveness of our approach is demonstrated in the context of travel time tomographic imaging using numerical and physical breast mimicking phantoms as well as patient data.

°For electrophysiology intervention monitoring, we intend to reconstruct 4D ultrasound (US) of structures in the beating heart from 2D transesophageal US by scanplane rotation. The image acquisition is continuous but unsynchronized to the heart rate, which results in a sparsely and irregularly sampled dataset and a spatiotemporal interpolation method is desired. Previously, we showed the potential of normalized convolution (NC) for interpolating such datasets. We explored 4D interpolation by 3 different methods: NC, nearest neighbor (NN), and temporal binning followed by linear interpolation (LTB). The test datasets were derived by slicing three 4D echocardiography datasets at random rotation angles (θ, range: 0-180) and random normalized cardiac phase (τ, range: 0-1). Four different distributions of rotated 2D images with 600, 900, 1350, and 1800 2D input images were created from all TEE sets. A 2D Gaussian kernel was used for NC and optimal kernel sizes (σθ and στ) were found by performing an exhaustive search. The RMS gray value error (RMSE) of the reconstructed images was computed for all interpolation methods. The estimated optimal kernels were in the range of σθ = 3.24 - 3.69°/ στ = 0.045 - 0.048, σθ = 2.79°/ στ = 0.031 - 0.038, σθ = 2.34°/ στ = 0.023 - 0.026, and σθ = 1.89°/ στ = 0.021 - 0.023 for 600, 900, 1350, and 1800 input images respectively. We showed that NC outperforms NN and LTB. For a small number of input images the advantage of NC is more pronounced.

In this paper we introduce and investigate an adaptive direct volume rendering (DVR) method for real-time visualization of cardiac 3D ultrasound. DVR is commonly used in cardiac ultrasound to visualize interfaces between tissue and blood. However, this is particularly challenging with ultrasound images due to variability of the signal within tissue as well as variability of noise signal within the blood pool. Standard DVR involves a global mapping of sample values to opacity by an opacity transfer function (OTF). While a global OTF may represent the interface correctly in one part of the image, it may result in tissue dropouts, or even artificial interfaces within the blood pool in other parts of the image. In order to increase correctness of the rendered image, the presented method utilizes blood pool statistics to do regional adjustments of the OTF. The regional adaptive OTF was compared with a global OTF in a dataset of apical recordings from 18 subjects. For each recording, three renderings from standard views (apical 4-chamber (A4C), inverted A4C (IA4C) and mitral valve (MV)) were generated for both methods, and each rendering was tuned to the best visual appearance by a physician echocardiographer. For each rendering we measured the mean absolute error (MAE) between the rendering depth buffer and a validated left ventricular segmentation. The difference d in MAE between the global and regional method was calculated and t-test results are reported with significant improvements for the regional adaptive method (d_A4C = 1.5 ± 0.3 mm, d_IA4C = 2.5 ± 0.4 mm, d_MV = 1.7 ± 0.2 mm, d.f. = 17, all p < 0.001). This improvement by the regional adaptive method was confirmed through qualitative visual assessment by an experienced physician echocardiographer who concluded that the regional adaptive method produced rendered images with fewer tissue dropouts and less spurious structures inside the blood pool in the vast majority of the renderings. The algorithm has been implemented on a GPU, running an average of 16 fps with a resolution of 512x512x100 samples (Nvidia GTX460).

Purpose: Patient-specific shape analysis of the mitral valve from real-time 3D ultrasound (rt-3DUS) has broad application to the assessment and surgical treatment of mitral valve disease. Our goal is to demonstrate that continuous medial representation (cm-rep) is an accurate valve shape representation that can be used for statistical shape modeling over the cardiac cycle from rt-3DUS images. Methods: Transesophageal rt-3DUS data acquired from 15 subjects with a range of mitral valve pathology were analyzed. User-initialized segmentation with level sets and symmetric diffeomorphic normalization delineated the mitral leaflets at each time point in the rt-3DUS data series. A deformable cm-rep was fitted to each segmented image of the mitral leaflets in the time series, producing a 4D parametric representation of valve shape in a single cardiac cycle. Model fitting accuracy was evaluated by the Dice overlap, and shape interpolation and principal component analysis (PCA) of 4D valve shape were performed. Results: Of the 289 3D images analyzed, the average Dice overlap between each fitted cm-rep and its target segmentation was 0.880±0.018 (max=0.912, min=0.819). The results of PCA represented variability in valve morphology and localized leaflet thickness across subjects. Conclusion: Deformable medial modeling accurately captures valve geometry in rt-3DUS images over the entire cardiac cycle and enables statistical shape analysis of the mitral valve.

Acquisition of a clinically acceptable scan plane is a pre-requisite for ultrasonic measurement of anatomical features from B-mode images. In obstetric ultrasound, measurement of gestational age predictors, such as biparietal diameter and head circumference, is performed at the level of the thalami and cavum septum pelucidi. In an accurate scan plane, the head can be modeled as an ellipse, the thalami looks like a butterfly, the cavum appears like an empty box and the falx is a straight line along the major axis of a symmetric ellipse inclined either parallel to or at small angles to the probe surface. Arriving at the correct probe placement on the mother's belly to obtain an accurate scan plane is a task of considerable challenge especially for a new user of ultrasound. In this work, we present a novel automated learning-based algorithm to identify an acceptable fetal head scan plane. We divide the problem into cranium detection and a template matching to capture the composite "butterfly" structure present inside the head, which mimics the visual cues used by an expert. The algorithm uses the stateof- the-art Active Appearance Models techniques from the image processing and computer vision literature and tie them to presence or absence of the inclusions within the head to automatically compute a score to represent the goodness of a scan plane. This automated technique can be potentially used to train and aid new users of ultrasound.

We present a new model-based framework for coupled segmentation and de-noising of medical images. The segmentation and de-noising steps are coupled through a discrete formulation of the total variation de-noising problem in a restricted setting such that each pixel in the image has its de-noised intensity level selected from a drastically reduced set of intensities. By creating such a reduced set of intensity levels, in which each intensity level represent the intensity across a region to be segmented, the intensity value for each de-noised pixel will be forced to assume a value in this limited set; by associating all pixels with the same de-noised value as a single region, image segmentation is naturally achieved. We derive two formulations corresponding to two noise models: additive white Gaussian and multiplicative Rayleigh. We furthermore show that the proposed framework enables globally optimal foreground/background segmentation of images with Rayleigh distributed noise.

Intraplaque neovascularization (IPN) has been linked with progressive atherosclerotic disease and plaque instability in several studies. Quantification of IPN may allow early detection of vulnerable plaques. A dedicated motion compensation method with normalized-cross-correlation (NCC) block matching combined with multidimensional (2D+time) dynamic programming (MDP) was developed for quantification of IPN in small plaques (<30% diameter stenosis). The method was compared to NCC block matching without MDP (forward tracking (FT)) and showed to improve motion tracking. Side-by-side CEUS and B-mode ultrasound images of carotid arteries were acquired by a Philips iU22 system with a L9-3 linear array probe. The motion pattern for the plaque region was obtained from the Bmode images with MDP. MDP results were evaluated in-vitro by a phantom and in-vivo by comparing to manual tracking of three experts for multibeat-image-sequences (MIS) of 11 plaques. In the in-vivo images, the absolute error was 72±55μm (mean±SD) for X (longitudinal) and 34±23μm for Y (radial). The method's success rate was visually assessed on 67 MIS. The tracking was considered failed if it deviated >2 pixels (~200μm) from true motion in any frame. Tracking was scored as fully successful in 63 MIS (94%) for MDP vs. 52(78%) for FT. The range of displacement over these 63 was 1045±471μm (X) and 395±216μm (Y). The tracking sporadically failed in 4 MIS (6%) due to poor image quality, jugular vein proximity and out-of-plane motion. Motion compensation showed improved lumen-plaque contrast separation. In conclusion, the proposed method is sufficiently accurate and successful for in vivo application.

X-wave is a particular case of limited diffracting waves which has great potential applications in the enlargement of the field depth in acoustic imaging systems. In practice, the generation of real time X-wave ultrasonic fields is a complex technology which involves precise and specific voltage for the excitations for each distinct array element. In order to simplify the X-wave generating process, L. Castellanos proposed an approach to approximate the X-wave excitations with rectangular pulses. The results suggested the possibility of achieving limited-diffraction waves with relatively simple driving waveforms, which could be implemented with a moderate cost in analogical electronics. In this work, we attempt to improve L. Castellanos's method by calculating the approximation driving pulse not only from rectangular but also triangular driving pulse. The differences between theoretical X-wave signals and driving pulses, related to their excitation effects, are minimized by L2 curve criterion. The driving pulses with the minimal optimization result we chosen. A tradeoff is obtained between the cost of implementation of classical 0-order X-wave and the precision of approximation with the simple pulsed electrical driving. The good agreement of the driving pulse and the result resulting field distributions, with those obtained from the classical X-wave excitations can be justified by the filtering effects induced by the transducer elements in frequency domain. From the simulation results, we can see that the new approach improve the precise of the approximation, the difference between theoretical X-wave and the new approach is lower 10 percent than the difference between theoretical X-wave and rectangular as the driving pulse in simulation.

Delay-and-sum (DAS) beamformer is extensively used in ultrasound imaging. However, the DAS beamformed signals have wide main lobe widths and high side lobe levels, which result in images with limited resolution and low contrast. Recently, a new signal processing method named phase coherence imaging (PCI) for side and grating lobes suppression was proposed. It was based on a statistical analysis of the phase dispersion in the received signals. The contrast could be significantly enhanced. For spatial resolution improvement, adaptive minimum variance (MV)-based beamformer presented in the ultrasound imaging literatures shows great potentials by minimizing off-axis signals, while keeping on-axis ones. In this paper, MV beamforming combined with PCI is introduced to effectively increase the imaging resolution and contrast simultaneously and outperform both MV and PCI beamformers. Two phase coherence factors, the phase coherence factor (PCF) and the sign coherence factor (SCF), are computed based on the measurement of the phase diversity of the received aperture data, and then used to weight the MV beamformed channel sum output. Simulations with point and cyst phantoms using FIELD II demonstrate the expected performance of the proposed beamforming method.

Explososcan is the 'gold standard' for real-time 3D medical ultrasound imaging. In this paper, 3D synthetic aperture imaging is compared to Explososcan by simulation of 3D point spread functions. The simulations mimic a 32×32 element prototype transducer. The transducer mimicked is a dense matrix phased array with a pitch of 300 μm, made by Vermon. For both imaging techniques, 289 emissions are used to image a volume spanning 60° in both the azimuth and elevation direction and 150mm in depth. This results for both techniques in a frame rate of 18 Hz. The implemented synthetic aperture technique reduces the number of transmit channels from 1024 to 256, compared to Explososcan. In terms of FWHM performance, was Explososcan and synthetic aperture found to perform similar. At 90mm depth is Explososcan's FWHM performance 7% better than that of synthetic aperture. Synthetic aperture improved the cystic resolution, which expresses the ability to detect anechoic cysts in a uniform scattering media, at all depths except at Explososcan's focus point. Synthetic aperture reduced the cyst radius, R_20dB, at 90mm depth by 48%. Synthetic aperture imaging was shown to reduce the number of transmit channels by four and still, generally, improve the imaging quality.

The Capon Beamforming algorithm is an optimal spatial filtering algorithm used in various signal processing applications where excellent interference rejection performance is required, such as Radar and Sonar systems, Smart Antenna systems for wireless communications. Its lack of robustness, however, means that it is vulnerable to array calibration errors and other model errors. To overcome this problem, numerous robust Capon Beamforming algorithms have been proposed, which are much more promising for practical applications. In this paper, an FPGA implementation of a robust Capon Beamforming algorithm is investigated and presented. This realization takes an array output with 4 channels, computes the complex-valued adaptive weight vectors for beamforming with an 18 bit fixed-point representation and runs at a 100 MHz clock on Xilinx V4 FPGA. This work will be applied in our medical imaging project for breast cancer detection.

Ultrasound could be an attractive imaging modality for detecting breast microcalcifications, but it requires significant improvement in image resolution and quality. Recently, we have used tissue-equivalent phantoms to demonstrate that synthetic-aperture ultrasound has the potential to detect small targets. In this paper, we study the in vivo imaging capability of a real-time synthetic-aperture ultrasound system for detecting breast microcalcifications. This LANL's (Los Alamos National Laboratory's) custom built synthetic-aperture ultrasound system has a maximum frame rate of 25 Hz, and is one of the very first medical devices capable of acquiring synthetic-aperture ultrasound data and forming ultrasound images in real time, making the synthetic-aperture ultrasound feasible for clinical applications. We recruit patients whose screening mammograms show breast microcalcifications, and use LANL's synthetic-aperture ultrasound system to scan the regions with microcalcifications. Our preliminary in vivo patient imaging results demonstrate that synthetic-aperture ultrasound is a promising imaging modality for detecting breast microcalcifications.

Center frequency and bandwidth are two generic parameters used to characterize transmitted pulse profiles in B-mode ultrasonic imaging. Increasing either is generally thought to improve spatial resolution in the final image, but at a potential cost of lower signal-to-noise ratio, with no general understanding of where they are optimal. In this work we investigate their role in converting the acquired radio-frequency signal from a linear array into an envelope image. Statistics of the backscattered signal, based on Rayleigh-Sommerfeld diffraction theory, are used in an ideal observer calculation that quantifies the task-relevant information contained in the radio-frequency (RF) signal. We then compare two approaches to computing an envelope image. The first is a standard B-mode envelope from the complex analytic signal. The second approach processes RF through a Wiener filter before forming an analytic signal. Effects of envelope detection are measured by computing the ideal observer in the envelope domain using Smith-Wagner approximations. Over frequencies ranging from 3-15MHz and fractional bandwidths ranging from 20% to 80%, we find that information transfer in the envelope varies widely with task. There is a substantial loss of information in all conditions in the formation of a standard envelope. Efficiency relative to the RF ranges from 60% to less than 5%. The Weinerfiltered envelope images substantially improve efficiency in two of the three tasks investigated. In the third task, the results are mixed, but we argue that the Weiner filter may be improved substantially by retuning it to the interior of a lesion.

The abdominal aorta (AA) is predisposed to development of abdominal aneurysms (AAA), a focal dilatation with fatal consequences if left untreated. The blood flow patterns is thought to play an important role in the development of AAA. The purpose of this work is to investigate the blood flow patterns within a group of healthy volunteers (six females, eight males) aged 23 to 76 years to identify changes and differences related to age and gender. The healthy volunteers were categorized by gender (male/female) and age (below/above 35 years). Subject-specific flow and geometry data were acquired using the research interface on a Profocus ultrasound scanner (B-K Medical, Herlev, Denmark) and segmentation of 3D magnetic resonance angiography (Magnetom Trio, Siemens Healthcare, Erlangen, Germany). The largest average diameter was among the elderly males (19.7 (± 1.33) mm) and smallest among the young females (12.4 (± 0.605) mm). The highest peak systolic velocity was in the young female group (1.02 (± 0.336) m/s) and lowest in the elderly male group (0.836 (± 0.127) m/s). A geometrical change with age was observed as the AA becomes more bended with age. This also affects the blood flow velocity patterns, which are markedly different from young to elderly. Thus, changes in blood flow patterns in the AA related to age and gender are observed. Further investigations are needed to determine the relation between changes in blood flow patterns and AAA development.

In this study clinically relevant ultrasound images generated with synthetic aperture sequential beamforming (SASB) is compared to images generated with a conventional technique. The advantage of SASB is the ability to produce high resolution ultrasound images with a high frame rate and at the same time massively reduce the amount of generated data. SASB was implemented in a system consisting of a conventional ultrasound scanner connected to a PC via a research interface. This setup enables simultaneous recording with both SASB and conventional technique. Eighteen volunteers were ultrasound scanned abdominally, and 84 sequence pairs were recorded. Each sequence pair consists of two simultaneous recordings of the same anatomical location with SASB and conventional B-mode imaging. The images were evaluated in terms of spatial resolution, contrast, unwanted artifacts, and penetration depth of the ultrasound beam. Five ultrasound experts (radiologists) evaluated the sequence pairs in a side-by-side comparison, and the results show that image quality using SASB was better than conventional B-mode imaging. 73 % of the evaluations favored SASB, and a probability of 70 % was calculated for a new radiologist to prefer SASB over conventional imaging, if a new sequence was recorded. There was no significant difference in penetration depth.

Pectus excavatum is the most common congenital deformity of the anterior thoracic wall. The surgical correction of such deformity, using Nuss procedure, consists in the placement of a personalized convex prosthesis into sub-sternal position to correct the deformity. The aim of this work is the CT-scan substitution by ultrasound imaging for the pre-operative diagnosis and pre-modeling of the prosthesis, in order to avoid patient radiation exposure. To accomplish this, ultrasound images are acquired along an axial plane, followed by a rigid registration method to obtain the spatial transformation between subsequent images. These images are overlapped to reconstruct an axial plane equivalent to a CT-slice. A phantom was used to conduct preliminary experiments and the achieved results were compared with the corresponding CT-data, showing that the proposed methodology can be capable to create a valid approximation of the anterior thoracic wall, which can be used to model/bend the prosthesis.

This study compares the performance of two proven but very different machine learners, Naïve Bayes and logistic regression, for differentiating malignant and benign breast masses using ultrasound imaging. Ultrasound images of 266 masses were analyzed quantitatively for shape, echogenicity, margin characteristics, and texture features. These features along with patient age, race, and mammographic BI-RADS category were used to train Naïve Bayes and logistic regression classifiers to diagnose lesions as malignant or benign. ROC analysis was performed using all of the features and using only a subset that maximized information gain. Performance was determined by the area under the ROC curve, Az, obtained from leave-one-out cross validation. Naïve Bayes showed significant variation (Az 0.733 ± 0.035 to 0.840 ± 0.029, P < 0.002) with the choice of features, but the performance of logistic regression was relatively unchanged under feature selection (Az 0.839 ± 0.029 to 0.859 ± 0.028, P = 0.605). Out of 34 features, a subset of 6 gave the highest information gain: brightness difference, margin sharpness, depth-to-width, mammographic BI-RADs, age, and race. The probabilities of malignancy determined by Naïve Bayes and logistic regression after feature selection showed significant correlation (R²= 0.87, P < 0.0001). The diagnostic performance of Naïve Bayes and logistic regression can be comparable, but logistic regression is more robust. Since probability of malignancy cannot be measured directly, high correlation between the probabilities derived from two basic but dissimilar models increases confidence in the predictive power of machine learning models for characterizing solid breast masses on ultrasound.

Respiratory motion tracking has been issues for MR/CT imaging and noninvasive surgery such as HIFU and radiotherapy treatment when we apply these imaging or therapy technologies to moving organs such as liver, kidney or pancreas. Currently, some bulky and burdensome devices are placed externally on skin to estimate respiratory motion of an organ. It estimates organ motion indirectly using skin motion, not directly using organ itself. In this paper, we propose a system that measures directly the motion of organ itself only using ultrasound image. Our system has automatically selected a window in image sequences, called feature window, which is able to measure respiratory motion robustly even to noisy ultrasound images. The organ's displacement on each ultrasound image has been directly calculated through the feature window. It is very convenient to use since it exploits a conventional ultrasound probe. In this paper, we show that our proposed method can robustly extract respiratory motion signal with regardless of reference frame. It is superior to other image based method such as Mutual Information (MI) or Correlation Coefficient (CC). They are sensitive to what the reference frame is selected. Furthermore, our proposed method gives us clear information of the phase of respiratory cycle such as during inspiration or expiration and so on since it calculate not similarity measurement like MI or CC but actual organ's displacement.

Conventional sonography, which performs well in dense breast tissue and is comfortable and radiation-free, is not practical for screening because of its operator dependence and the time needed to scan the whole breast. While magnetic resonance imaging (MRI) can significantly improve on these limitations, it is also not practical because it has long been prohibitively expensive for routine use. There is therefore a need for an alternative breast imaging method that obviates the constraints of these standard imaging modalities. The lack of such an alternative is a barrier to dramatically impacting mortality (about 45,000 women in the US per year) and morbidity from breast cancer because, currently, there is a trade-off between the cost effectiveness of mammography and sonography on the one hand and the imaging accuracy of MRI on the other. This paper presents a progress report on our long term goal to eliminate this trade-off and thereby improve breast cancer survival rates and decrease unnecessary biopsies through the introduction of safe, cost-effective, operatorindependent sonography that can rival MRI in accuracy. The objective of the study described in this paper was to design and build an improved ultrasound tomography (UST) scanner in support of our goals. To that end, we report on a design that builds on our current research prototype. The design of the new scanner is based on a comparison of the capabilities of our existing prototype and the performance needed for clinical efficacy. The performance gap was quantified by using clinical studies to establish the baseline performance of the research prototype, and using known MRI capabilities to establish the required performance. Simulation software was used to determine the basic operating characteristics of an improved scanner that would provide the necessary performance. Design elements focused on transducer geometry, which in turn drove the data acquisition system and the image reconstruction engine specifications. The feasibility of UST established by our earlier work and that of other groups, forms the rationale for developing a UST system that has the potential to become a practical, low-cost device for breast cancer screening and diagnosis.

Breast cancer is the most common cancer among women. The established screening method to detect breast cancer in an early state is X-ray mammography. However, X-ray frequently provides limited contrast of tumors located within glandular tissue. A new imaging approach is Ultrasound Computer Tomography generating threedimensional volumes of the breast. Three different images are available: reflectivity, attenuation and speed of sound. The correlation of USCT volumes with X-ray mammograms is of interest for evaluation of the new imaging modality as well as for a multimodal diagnosis. Yet, both modalities differ in image dimensionality, patient positioning and deformation state of the breast. In earlier work we proposed a methodology based on Finite Element Method to register speed of sound images with the according mammogram. In this work, we enhanced the methodology to register all three image types provided by USCT. Furthermore, the methodology is now completely automated using image similarity measures to estimate rotations in datasets. A fusion methodology is proposed which combines the information of the three USCT image types with the X-ray mammogram via semitransparent overlay images. The evaluation was done using 13 datasets from a clinical study. The registration accuracy was measured by the displacement of the center of a lesion marked in both modalities. Using the automated rotation estimation, a mean displacement of 10.4 mm was achieved. Due to the clinically relevant registration accuracy, the methodology provides a basis for evaluation of the new imaging device USCT as well as for multimodal diagnosis.

It is known that breast cancer risk is greater in women with higher breast densities. Currently, breast density is measured using mammographic percent density, defined as the ratio of fibroglandular to total breast area on a two dimensional mammogram. Alternatively, systems that use ultrasound tomography (UST) create tomographic sound speed images of the patient's breast. These volumetric images can be useful as a diagnostic aid because it is also known that sound speed of tissue is proportional to the density of the tissue. The purpose of this work is to expand on the comparisons of the two imaging modalities by introducing new ultrasound tomography measurements that separate and quantify the fatty and dense tissue distributions within the breast. A total of 249 patients were imaged using both imaging modalities. By using k-means clustering, correlations beyond the volume averaged sound speed of the ultrasound images and the mammographic percent density were investigated. Both the ultrasound and mammographic images were separated into dense and fatty regions. Various associations between the global breast properties as well as separate tissue components were found.

A multi-grid tomographic inversion approach that uses variable grid sizes in both forward modeling and inverse process is proposed and tested on breast phantom data and breast ultrasound data. In iterative tomographic inversion, fine scale features are more sensitive to starting model than coarse scale features. The proposed multi-grid algorithm starts from coarse grids for both forward modeling and inverse process and gradually proceeds to fine grids, which can effectively suppress artifacts related to over iteration of fine scale features. Since the computational complexity of inverse problems increases with number of grid points in both forward model and inverse model, the proposed algorithm greatly reduces the computational cost in contrast to standard fixed-grid approaches. Both in vitro and in vivo results indicate that the proposed multi-grid methods result in significant improvement in the inverted sound speed and attenuation images compared to fixed-grid methods.

True three-dimensional (3D) volumetric ultrasound (US) acquisitions stand to benefit intraoperative neuronavigation on multiple fronts. While traditional two-dimensional (2D) US and its tracked, hand-swept version have been recognized for many years to advantage significantly image-guided neurosurgery, especially when coregistered with preoperative MR scans, its unregulated and incomplete sampling of the surgical volume of interest have limited certain intraoperative uses of the information that are overcome through direct volume acquisition (i.e., through 2D scan-head transducer arrays). In this paper, we illustrate several of these advantages, including image-based intraoperative registration (and reregistration) and automated, volumetric displacement mapping for intraoperative image updating. These applications of 3D US are enabled by algorithmic advances in US image calibration, and volume rasterization and interpolation for multi-acquisition synthesis that will also be highlighted. We expect to demonstrate that coregistered 3D US is well worth incorporating into the standard neurosurgical navigational environment relative to traditional tracked, hand-swept 2D US.

B-mode ultrasound is widely used in liver ablation. However, the necrosis zone is typically not visible under b-mode ultrasound, since ablation does not necessarily change the acoustic properties of the tissue. In contrast, the change in tissue stiffness makes elastography ideal for monitoring ablation. Tissue palpation for elastography is typically applied at the imaging probe, by indenting it slightly into the tissue surface. However, in this paper we propose an alternate approach, where palpation is applied by a surgical instrument located inside the tissue. In our approach, the ablation needle is placed inside a steerable device called an active cannula and inserted into the tissue. A controlled motion is applied to the center of the ablation zone via the active cannula. Since the type and direction of motion is known, displacement can then be computed from two frames with the desired motion. The elastography results show the ablated region around the needle. While internal palpation provides excellent local contrast, freehand palpation from outside of the tissue via the transducer can provide a more global view of the region of the interest. For this purpose, we used a tracked 3D transducer to generate volumetric elastography images covering the ablated region. The tracking information is employed to improve the elastography results by selecting volume pairs suitable for elastography. This is an extension of our 2D frame selection technique which can cope with uncertainties associated with intra-operative elastography. In our experiments with phantom and ex-vivo tissue, we were able to generate high-quality images depicting the boundaries of the hard lesions.

In Computer Assisted Orthopaedic Surgery (CAOS), surgeons have to acquire some anatomical landmarks as inputs to the system. To do so, they use manual pointers that are localized in the Operating Room (OR) space using an infrared camera. When the needed landmark is not reachable through an opening, it is palpated directly on skin and there is a loss of precision that can vary from several millimeters to centimeters depending on the thickness of soft tissues. In this paper, we propose a new framework based on three main steps to register the bone surface and extract automatically anatomical landmarks with an ultrasound probe. This framework is based on an oriented gradient calculation, a simulated-compound and a contour closure using a graph representation. The oriented gradient allows extracting a set of pixels that probably belong to the bone surface. The simulatedcompound step allows using ultrasound images properties to define a set of small segments which may belong to the bone surface, and the graph representation allows eliminating false positive detection among remaining segments. The proposed method has been validated on a database of 230 ultrasound images of anterior femoral condyles (on the knee). The average computation time is 0.11 sec per image, and average errors are: 0.54 mm for the bone surface extraction, 0.31 mm for the condylar line, and 1.4 mm for the trochlea middle.

There is growing interest in developing techniques to assess the structure and function of microvasculature, to enable clinical diagnosis and to gain insights into disease pathology. High-frequency subharmonic imaging is an emerging technique that can visualize the microvasculature with high specificity. However, the sensitivity of high-frequency subharmonic imaging is compromised because of the pressure threshold for subharmonic behavior, which may limit its potential for preclinical and clinical imaging. The goal of this work was to demonstrate that the sensitivity of subharmonic imaging could be improved by rectangular apodization and chirp-coding of the excitation pulse. We report an experimental study carried out at 20-MHz transmit frequency to compare the efficacy of narrowband sine bursts and coded-chirps towards generating subharmonics. It was demonstrated that chirp-coding of the excitation pulse could generate stable subharmonic signals for excitation bandwidths of 10-20%. The threshold for onset of subharmonic behavior was lowest when rectangularwindowed excitation pulses were employed. The subharmonic to fundamental ratio of RF spectra using coded chirps was up to 5.7 dB higher for sine bursts, and the axial resolution obtained with chirp-coded excitation was up to twofold better compared to that obtained using sine bursts. At 20-MHz transmit frequency, 20% bandwidth rectangular chirp-coded pulse appears to be a good tradeoff between sensitivity and axial resolution.

In this work the use of the self-demodulation (S-D) signal as a mean of microbubble excitation at the subharmonic (SH) frequency to enhance the SH emission of ultrasound contrast agent (UCA) is studied. SH emission from the UCA is of interest since it is produced only by the UCA and is free of the artifacts produced in harmonic imaging modes. The S-D wave is a low-frequency signal produced by nonlinear propagation of an ultrasound wave in the medium. Single element transducer experiments and numerical simulations were conducted at 10 MHz to study the effect of the S-D signal on the SH response of the UCA by modifying the envelope of the excitation bursts. For 6 and 20 transmitted cycles, the SH response is increased up to 25 dB and 22 dB because of the S-D stimulation for a burst with a rectangular envelope compared with a Gaussian envelope burst. Such optimized excitations were used in an array-based micro-ultrasound system (Vevo 2100, VisualSonics Inc., Toronto, ON, Canada) at 18 MHz for in vitro validation of SH imaging. This study suggests that a suitable design of the envelope of the transmit excitation to generate a S-D signal at the SH frequency can enhance the SH emission of UCA and real-time SH imaging is feasible with shorter transmit burst (6- cycle) and low acoustic pressure (~150 KPa) at high frequencies (>15 MHz).

Contrast-enhanced ultrasound (CEUS) is a rapid and inexpensive medical imaging technique to assess tissue perfusion with a high temporal resolution. It is composed of a sequence with ultrasound brightness values and a contrast sequence acquired simultaneously. However, the image acquisition is disturbed by various motion influences. Registration is needed to obtain reliable information of spatial correspondence and to analyze perfusion characteristics over time. We present an approach to register an ultrasonography sequence by using a feature label map. This label map is generated from the b-mode data sequence by a Markov-Random-Field (MRF) based analysis, where each location is assigned to one of the user-defined regions according to its statistical parameters. The MRF reduces the chance that outliers are represented in the label map and provides stable feature labels over the time frames. A registration consisting of rigid and non-rigid transformations is determined consecutively using the generated label map of the respective frames for similarity calculation. For evaluation, the standard deviation within specific regions in intestinal CEUS images has been measured before and after registration resulting in an average decrease of 8.6 %. Additionally, this technique has proven to be more robust against noise influence compared to similarity calculation based on image intensities only. The latter leads only to 7.6 % decrease of the standard deviation.

The in vivo performance of a Fluorescence Molecular Tomography system as a function of pathophysiological parameters that determine the penetration of nonbinding fluorescent nanoparticle was examined through imaging of a series of three tumor models. The pathophysiological parameters examined were, vessel density, interstitial fluid pressure (IFP), and collagen content. Drug delivery and IFP were measured in vivo via fluorescence spectroscopy and a fiber-optic coupled pressure probe. Vessel density and collagen content were determined ex vivo through histochemical analysis. The kinetics of the 40 nm,10000 KDa, fluorescent particles, which were injected into the tail vein of the mice, was monitored by sequential excitation of the tissue on and off the tumor site through employment of sixteen source detector pairs interspersed linearly in reflectance geometry. Each optical fluorescence data set was collected at discrete time intervals in order to monitor drug uptake for a period of 45 minutes. The kinetics of the drug delivery and the average nanoparticle uptake were correlated with the vessel density, interstitial pressure and collagen content. The results of the correlations were verified to be consistent with the published relationship between the three pathophysiological parameters and nanoparticle drug delivery.

Elastography is a non-invasive imaging technique that images tissue stiffness. Given the well known association between tissue stiffness and cancer type, it can be used effectively for breast cancer detection and assessment. This study involves system development of a real-time ultrasound based elastography system designed for assessing multifocal breast cancer. This system is capable of imaging breast tissues absolute Young's Moduli. The imaging involves tissue mechanical stimulation, displacement and force data acquisition followed by Young's modulus reconstruction using a constrained full-inversion approach. This approach utilizes axial strain field and surface force data acquired by the elastography system via an iterative numerical process to construct the breast tissue Young's modulus. The strain field is obtained using an ultrasound machine equipped with an RF signal processing module. For force data acquisition, a system comprised of two load cells attached at the ultrasound system probe was employed. Each iteration of the reconstruction algorithm involves tissue stress calculation followed by tissue Young's modulus updating. To speed up the reconstruction process, a novel accelerated finite element method developed in our laboratory was used for stress calculation. To validate the proposed method, tissue-mimicking phantom studies were conducted. These studies showed promising results paving the way for further validation and application in a clinical setting.

Ultrasound image has already been proved to be a useful tool for non-invasive strain quantifications in soft tissue. While clinical applications only include cardiac imaging, the development of techniques suitable for musculoskeletal system is an active area of research. On this study, a technique for speckle tracking on ultrasound images using non-rigid image registration is presented. This approach is based on a single 2D+t registration procedure, in which the temporal changes on the B-mode speckle patterns are locally assessed. This allows estimating strain from ultrasound image sequences of tissues under deformation while imposing temporal smoothness in the deformation field, originating smooth strain curves. METHODS: The tracking algorithm was systematically tested on synthetic images and gelatin phantoms, under sinusoidal deformations with amplitudes between 0.5% and 4.0%, at frequencies between 0.25Hz and 2.0Hz. Preliminary tests were also performed on Achilles tendons isolated from human cadavers. RESULTS: The strain was estimated with deviations of -0.011%±0.053% on the synthetic images and agreements of ±0.28% on the phantoms. Some tests with real tendons show good tracking results. However, significant variability between the trials still exists. CONCLUSIONS: The proposed image registration methodology constitutes a robust tool for motion and deformation tracking in both simulated and real phantom data. Strain estimation in both cases reveals that the proposed method is accurate and provides good precision. Although the ex-vivo results are still preliminary, the potential of the proposed algorithm is promising. This suggests that further improvements, together with systematic testing, can lead to in-vivo and clinical applications.

An estimated 82 million American adults have one or more type of cardiovascular diseases (CVD). CVD is the leading cause of death (1 of every 3 deaths) in the United States. When considered separately from other CVDs, stroke ranks third among all causes of death behind diseases of the heart and cancer. Stroke accounts for 1 out of every 18 deaths and is the leading cause of serious long-term disability in the United States. Motion estimation of ultrasound videos (US) of carotid artery (CA) plaques provides important information regarding plaque deformation that should be considered for distinguishing between symptomatic and asymptomatic plaques. In this paper, we present the development of verifiable methods for the estimation of plaque motion. Our methodology is tested on a set of 34 (5 symptomatic and 29 asymptomatic) ultrasound videos of carotid artery plaques. Plaque and wall motion analysis provides information about plaque instability and is used in an attempt to differentiate between symptomatic and asymptomatic cases. The final goal for motion estimation and analysis is to identify pathological conditions that can be detected from motion changes due to changes in tissue stiffness.

An ultrasound vector Doppler imaging is useful for detecting flow components normal to the ultrasound beam direction. However, the conventional vector Doppler imaging method suffers from the bias of the time interval between samples caused by the mismatch between transmit and receive directions during demodulation. In this paper, a new directional demodulation method, in which demodulation is performed with a modified sample interval depending on the receive beam steered angle to reduce the bias occurred in a conventional ultrasound vector Doppler imaging is presented. To evaluate the performance of the proposed directional demodulation method, the pre-beamformed radio-frequency (RF) data from in-vitro experiments were obtained using a commercial ultrasound system and a Doppler string phantom. The true flow velocity of the phantom was 0.3 m/s. The center frequency of 5 MHz and the pulse repetition frequency of 4 kHz were used for the experiments. Also, a 32-element sub-aperture on a 128-element 7.2-MHz linear array probe were used for emission and reception while changing the flow direction from -45 degrees to 0 degree by a step of 5 degrees. The proposed directional demodulation method successfully visualizes all flow directions. In addition, it lowers a bias on flow estimation compared to the conventional method (i.e., 0.0255±0.0516 m/s vs. 0.0248±0.0469 m/s of error of velocity, 2.4862±3.8911 degrees vs. 2.4857±3.5115 degrees of error of direction, respectively). These results indicate that the proposed directional demodulation method can enhances the accuracy in flow estimation for vector Doppler imaging.

The established standard screening method to detect breast cancer is X-ray mammography. However X-ray mammography often has low contrast for tumors located within glandular tissue. A new approach is 3D Ultrasound Computer Tomography (USCT), which is expected to detect small tumors at an early stage. This paper describes the development, improvement and the results of Finite Element Method (FEM) simulations of the Transducer Array System (TAS) used in our 3D USCT. The focus of this work is on researching the influence of meshing and material parameters on the electrical impedance curves. Thereafter, these findings are used to optimize the simulation model. The quality of the simulation was evaluated by comparing simulated impedance characteristics with measured data of the real TAS. The resulting FEM simulation model is a powerful tool to analyze and optimize transducer array systems applied for USCT. With this simulation model, the behavior of TAS for different geometry modifications was researched. It provides a means to understand the acoustical performances inside of any ultrasound transducer represented by its electrical impedance characteristic.

Speed of sound imaging is an important modality used in medical ultrasound applications. We developed a 3D ultrasound computer tomograph (3D USCT) which is capable of reflection and transmission tomography. Most 3D tomography reconstruction methods like the algebraic reconstruction technique rely on the assumption that the transmission rays propagate straightly from emitter to receiver, which is not valid for ultrasound. Due to refractions in the tissue the rays are bent rather than straight. To overcome this problem we use a 3D Eikonal solver that calculates the bent ray paths for the transmission pulses and include it into our Compressive Sampling reconstruction framework. Using an iterative scheme we show results for synthetic and real data. The shape and the outline of the phantoms reconstructed with the bent-ray method match the reflection reconstructions better and for synthetic data the speed of sound is closer to the speed of sound in the phantom by approximately 1.2 m/s.

A Monte Carlo model of ultrasound modulation of multiply scattered coherent light in a highly scattering media has been carried out for estimating the phase shift experienced by a photon beam on its transit through US insonified region. The phase shift is related to the tissue stiffness, thereby opening an avenue for possible breast tumor detection. When the scattering centers in the tissue medium is exposed to a deterministic forcing with the help of a focused ultrasound (US) beam, due to the fact that US-induced oscillation is almost along particular direction, the direction defined by the transducer axis, the scattering events increase, thereby increasing the phase shift experienced by light that traverses through the medium. The phase shift is found to increase with increase in anisotropy g of the medium. However, as the size of the focused region which is the region of interest (ROI) increases, a large number of scattering events take place within the ROI, the ensemble average of the phase shift (Δφ) becomes very close to zero. The phase of the individual photon is randomly distributed over 2π when the scattered photon path crosses a large number of ultrasound wavelengths in the focused region. This is true at high ultrasound frequency (1 MHz) when mean free path length of photon l_s is comparable to wavelength of US beam. However, at much lower US frequencies (100 Hz), the wavelength of sound is orders of magnitude larger than ls, and with a high value of g (g 0.9), there is a distinct measurable phase difference for the photon that traverses through the insonified region. Experiments are carried out for validation of simulation results.

In medical diagnosis, use of elastography is becoming increasingly more useful. However, treatments usually assume a planar compression applied to tissue surfaces and measure the deformation. The stress distribution is relatively uniform close to the surface when using a large, flat compressor but it diverges gradually along tissue depth. Generally in prostate elastography, the transrectal probes used for scanning and compression are cylindrical side-fire or rounded end-fire probes, and the force is applied through the rectal wall. These make it very difficult to detect cancer in prostate, since the rounded contact surfaces exaggerate the non-uniformity of the applied stress, especially for the distal, anterior prostate. We have developed a preliminary 2D Finite Element Model (FEM) to simulate prostate deformation in elastography. The model includes a homogeneous prostate with a stiffer tumor in the proximal, posterior region of the gland. A force is applied to the rectal wall to deform the prostate, strain and stress distributions can be computed from the resultant displacements. Then, we assume the displacements as boundary condition and reconstruct the modulus distribution (inverse problem) using linear perturbation method. FEM simulation shows that strain and strain contrast (of the lesion) decrease very rapidly with increasing depth and lateral distance. Therefore, lesions would not be clearly visible if located far away from the probe. However, the reconstructed modulus image can better depict relatively stiff lesion wherever the lesion is located.

Fully developed speckle has been used previously to estimate the out-of-plane motion of ultrasound images. However, in real tissue the rarity of such patterns and the presence of coherency diminish both the precision and the accuracy of the out-of-plane motion estimation. In this paper, for the first time, we propose a simple mathematical derivation for out-of-plane motion estimation in which the coherent and non-coherent parts of the RF echo signal are separated. This method is based on the Rician-Inverse Gaussian stochastic model of the speckle formation process, which can be considered as a generalized form of the K-distribution with richer parameterization. The flexibility of the proposed method allows considering any patch of the RF echo signal for the purpose of displacement estimation. The experimental results on real tissue demonstrate the potential of the proposed method for accurate out-of-plane estimation. The underestimation of motion in ex vivo bovine tissue at 1 mm displacement is reduced to 15.5% compared to 37% for a base-line method.

Research requiring the murine pancreatic duct to be imaged is often challenging due to the difficulty in selectively cannulating the pancreatic duct. We have successfully catheterized the pancreatic duct through the common bile duct in severe combined immune deficient (SCID) mice and imaged the pancreatic duct with gas filled lipid microbubbles that increase ultrasound imaging sensitivity due to exquisite scattering at the gas/liquid interface. A SCID mouse was euthanized by CO₂, a midline abdominal incision made, the common bile duct cut at its midpoint, a 2 cm, 32 gauge tip catheter was inserted about 1 mm into the duct and tied with suture. The duodenum and pancreas were excised, removed in toto, embedded in agar and an infusion pump was used to instill normal saline or lipid-coated microbubbles (10 million / ml) into the duct. B-mode images before and after infusion of the duct with microbubbles imaged the entire pancreatic duct (~ 1 cm) with high contrast. The microbubbles were cavitated by high mechanical index (HMI) ultrasound for imaging to be repeated. Our technique of catheterization and using lipid microbubbles as a contrast agent may provide an effective, affordable technique of imaging the murine pancreatic duct; cavitation with HMI ultrasound would enable repeated imaging to be performed and clustering of targeted microbubbles to receptors on ductal cells would allow pathology to be localized accurately. This research was supported by the Experimental Mouse Shared Service of the AZ Cancer Center (Grant Number P30CA023074, NIH/NCI and the GI SPORE (NIH/NCI P50 CA95060).

Time-reversal with Multiple Signal Classification (TR-MUSIC) is an ultrasound imaging algorithm for detecting small targets embedded in a medium. This technique can produce images with subwavelength resolution when the targets are pointlike, and when the number of targets is fewer than the number of transducer elements used to image the medium. In this experimental study, we evaluate the performance of the TR-MUSIC algorithm when the interrogated medium contains extended targets that cannot be considered as point scatterers. We construct tissue-mimicking phantoms embedded with distributed glass spheres. We show that the quality of the phantom images obtained using the TR-MUSIC algorithm decreases with increasing sphere size. However, significant improvement is achieved when the image plane is divided into sub-regions, where each sub-region is imaged separately. The windowed TR-MUSIC algorithm accurately locates the spheres (extended targets), but the images do not provide quantitative information about the shape and reflectivity of the spheres.

This paper describes the design and implementations of the complete 2D capacitive micromachined ultrasound transducer electronics and its analog front-end module for transmitting high voltage ultrasound pulses and receiving its echo signals to realize 3D ultrasound image. In order to minimize parasitic capacitances and ultimately improve signal-to- noise ratio (SNR), cMUT has to be integrate with Tx/Rx electronics. Additionally, in order to integrate 2D cMUT array module, significant optimized high voltage pulser circuitry, low voltage analog/digital circuit design and packaging challenges are required due to high density of elements and small pitch of each element. We designed 256(16x16)- element cMUT and reconfigurable driving ASIC composed of 120V high voltage pulser, T/R switch, low noise preamplifier and digital control block to set Tx frequency of ultrasound and pulse train in each element. Designed high voltage analog ASIC was successfully bonded with 2D cMUT array by flip-chip bonding process and it connected with analog front-end board to transmit pulse-echo signals. This implementation of reconfigurable cMUT-ASIC-AFE board enables us to produce large aperture 2D transducer array and acquire high quality of 3D ultrasound image.

In medical ultrasound imaging, dynamic receive beamforming has been used for improving signal-to-noise ratio (SNR) and spatial resolution. For low-cost portable ultrasound imaging systems, a fractional filter-based receive beamforming (FFRB) method was previously proposed to reduce the hardware complexity compared to conventional interpolation filter-based receive beamforming methods (IFRB). While this new beamforming method substantially reduces the hardware complexity, it yields the nonlinear phase response for high frequencies due to the limited length of fractional filter coefficients, leading to the bias on flow estimation in ultrasound color Doppler imaging. In this paper, to evaluate the FFRB method for ultrasound color Doppler imaging, the Field II simulation and string phantom experiments were conducted. In Field II simulation, the radio-frequency (RF) data were generated by assuming a 7.5-MHz linear array probe with the transmit frequency of 6 MHz, the ensemble size of 8, and the sampling frequencies of 20 MHz. In string phantom experiments, the RF channel data were obtained with a commercial SonixTouch ultrasound scanner equipped with a research package (Ultrasonix Corp., Vancouver, BC, Canada) and a 5-MHz linear array connected to a SonixDAQ parallel system. The ensemble size and the sampling frequency were set to 10 and 20 MHz, respectively. For the Field II simulation and string phantom experiments, only 1.2% and 2.3 % in color Doppler estimation error ratio was observed with mean and standard deviation along the lateral direction. This result indicates that the proposed FFRB method could be utilized for a low-cost ultrasound color Doppler imaging system with lowered hardware complexity and minimized phase errors.

Synthetic aperture (SA) imaging techniques can enhance spatial resolution in medical ultrasound imaging. However, it suffers from the degradation of image quality close to a virtual source (e.g., transmit focal point) since there is no enough transmit acoustic field energy. In this paper, a new SA imaging technique (i.e., dynamic synthetic aperture, DSA) where the number of synthetic scanlines for acoustic field superposition is dynamically adjusted based on the transmit acoustic field analysis. For the DSA technique, the dynamic apodization window function was generated from the Field II simulation and applied in the phantom and in vivo experiments. The raw radio-frequency (RF) data for phantom and in vivo experiments were captured by an Ultrasonix's SonixTouch research platform connected with a SonixDAQ parallel acquisition system. From the phantom experiment, the proposed DSA method shows the enhanced spatial resolution over the depth compared to the conventional receive dynamic focusing (CRDF). In addition, it doesn't yield any artifacts associated with the lack of enough transmit acoustic energy shown in the conventional SA imaging technique. The consistent results were obtained with the in vivo breast data. This result indicates that the proposed DSA method could be used for enhancing image quality of medical ultrasound imaging.

Direct pixel beamforming (DPB) where receive focusing is directly performed on each display pixel in Cartesian coordinates using the raw radio-frequency (RF) data can improve spatial and contrast resolutions in medical ultrasound imaging. However, the DPB suffers from the increased computational complexity compared to the conventional delay-and- sum focusing (CON) method since it requires additional focusing points for envelop detection. In this paper, a new DPB method, in which phase rotation (PR) is adopted for reducing the number of the additional focusing points, is presented. In the proposed DPB-PR method, the complex baseband data for each display pixel is directly obtained for envelop detection, so that the unnecessary focusing points can be avoided. To evaluate the performance of the DPB-PR method, in vitro raw RF data were captured from a tissue mimicking phantom using the SonixTouch research platform connected with the SonixDAQ parallel data acquisition system. The hardware saving from the DPB-PR method was compared with the DPB method with interpolation filtering (DPB-INT) method by analyzing the number multiplications. Compared to CON, the proposed DPB-PR method shows enhanced image quality (clear shape and boundaries of masses) under visual assessment and comparable results with the DPB-INT method. Furthermore, the proposed DPB-PR method significantly reduces the number of multiplications by a factor of 3.1 (i.e., 9.0×10⁹ vs 2.9×10⁹ ) over the DPB-INT method. This result indicates that the DPB-PR method can be implemented on a modern ultrasound imaging system while improving image quality.

The concern with interstitial ablative therapy for a treatment of hepatic tumors has been growing. In spite of advances in these therapies, there are several technical challenges due to tissue deformation and target motion: localization of the tumor and monitoring for ablator's tip and thermal dose in heated tissue. In the previous work, a steerable acoustic ablator, called ACUSITT, for targeting of ablation tip accurately into tumor area has been developed. However, real-time monitoring techniques for providing image feedback of the ablation tip positioning and thermal dose deposited in the tissue by heating are still needed. In this paper, a new software framework for real-time monitoring ablative therapy during pre- and intra-operation is presented. The software framework provides ultrasound Brightness Mode (B-Mode) image and elastography simultaneously and with real-time. A position of ablator's tip and a region of heated tissue are monitored on B-Mode image, because the image represents tissue morphology. Furthermore, ultrasound elasticity image is used for finding a boundary and region of tumor on pre-ablation, and monitoring thermal dose in tissue during ablation. By providing B-Mode image and elastography at the same time, reliable information for monitoring thermal therapy can be offered.

Acquisition of pre-beamformed data is essential in advanced imaging research studies such as adaptive beamforming, synthetic aperture imaging, and photoacoustic imaging. Ultrasonix Co. has developed such a data acquisition device for pre-beamformed data known as the SONIX-DAQ, but data can only be downloaded and processed offline rather than streamed in real-time. In this work, we developed a software framework to extend the functionality of the SONIX-DAQ for streaming and processing data in near real-time. As an example, we applied this functionality to our previous work of visualizing photoacoustic images of prostate brachytherapy seeds. In this paper, we present our software framework, applying it to a real-time photoacoustic imaging system, including real-time data collection and data-processing software modules for brachytherapy treatment.

High resolution medical ultrasound imaging is an ongoing challenge in many diagnosis applications and can be achieved by instrumentation. Very few works have investigated ultrasound image resolution enhancement whereas many works regarded general purpose optical image or video fields. Many algorithms were proposed within these fields to achieve the "super-resolution" (SR), which consists in merging several low resolution images to create a higher resolution image. However, the straightforward implementation of such techniques for ultrasound imaging is unsuccessful, due to the intrinsic nature of ultrasound motions and speckle. We show how to overcome the intrinsic limit of super-resolution in this framework by refining the registration part of common multi-frame techniques. Classic super-resolution algorithms were implemented and evaluated using sequences of ultrasound images. Such methods not only fail to estimate the true elastic motion but also break the speckle characteristics, resulting in a degradation of the original image. Knowing that a registration error of only 1 pixel leads to a high-resolution image worse than an interpolation, the registration must be adapted to the framework of ultrasound imaging. For this purpose, we investigate different motion estimations. The process described above was evaluated on ultrasound sequences containing up to 15 phantom images with an inclusion scanned with a 7.5 MHz linear probe. Qualitative improvements were observable as soon as at least 5 low-resolution images were used. Ultrasound B-mode profiles of radio-frequency lines were studied and the inclusion was more accurately identified. The Contrast-to-Noise Ratio was increased by approximately 13%.

Breast cancer is one of the leading causes of cancer mortality among women. Ultrasound examination can be used to assess breast masses, complementarily to mammography. Ultrasound images reveal tissue information in its echoic patterns. Therefore, pattern recognition techniques can facilitate classification of lesions and thereby reduce the number of unnecessary biopsies. Our hypothesis was that image texture features on the boundary of a lesion and its vicinity can be used to classify masses. We have used intensity-independent and rotation-invariant texture features, known as Local Binary Patterns (LBP). The classifier selected was K-nearest neighbors. Our breast ultrasound image database consisted of 100 patient images (50 benign and 50 malignant cases). The determination of whether the mass was benign or malignant was done through biopsy and pathology assessment. The training set consisted of sixty images, randomly chosen from the database of 100 patients. The testing set consisted of forty images to be classified. The results with a multi-fold cross validation of 100 iterations produced a robust evaluation. The highest performance was observed for feature LBP with 24 symmetrically distributed neighbors over a circle of radius 3 (LBP_24,3) with an accuracy rate of 81.0%. We also investigated an approach with a score of malignancy assigned to the images in the test set. This approach provided an ROC curve with Az of 0.803. The analysis of texture features over the boundary of solid masses showed promise for malignancy classification in ultrasound breast images.

The ultrasound radio-frequency (RF) time series method has been shown to be an effective approach for accurate tissue classification and cancer detection. Previous studies of the RF time series method were based on a serial MATLAB implementation of feature calculation that involved long running times. Clinical applications of the RF time series method require a fast and efficient implementation that enables realistic imaging studies within a short time frame. In this paper, a parallel implementation of the RF time series method is developed to support clinical ultrasound imaging studies. The parallel implementation uses a Graphics Processing Unit (GPU) to compute the tissue classification features of the RF time series method. Moreover, efficient graphical representations of the RF times series features are obtained using the Qt framework. Tread computing is used to concurrently compute and visualize the RF time series features. The parallel implementation of the RF time series is evaluated for various configurations of number of frames and number of scan lines per frame acquired in an imaging study. Results demonstrate that the parallel implementation enables imaging of tissue classification at interactive time. A typical RF time series of 128 frames and 128 scan lines per frame, the parallel implementation be processed in 0.8128 ± 0.0420 sec.

A new method for reducing the speckle in ultrasound images is introduced, which is an adaptation of Non Local Means filter by incorporating nonlinear Gaussian for identifying the similarity of patches and restoration of pixel value. By using this method, we are able to achieve speckle removal without using filter chains which was otherwise required for Non linear Gaussian filters for considerable noise removal. User interaction is facilitated for controlling the amount of noise removal and smoothing. The overall time required for computations is less and the accuracy and quality of the images is preserved. The algorithm has been tested on phantom data as well as in vivo data. The performance measure is evaluated based on standard evaluation parameters. On visually comparing the despeckled images, it can be found that the structure and edge information is preserved while suppressing the speckle. Experimental results prove that this method can be used for removing speckle in medical ultrasound images without compromising the accuracy and quality. There are two tunable parameters in this filter. They are for controlling the amount of noise removal and smoothing. This makes it possible for the user to adjust the amount of filtering. The filter can be easily extended to three dimensions there by facilitating 3D volume filtering. The filter can be easily implemented in GPU (Graphics Processing Units) which makes it possible to be used in real time particularly for volume rendering and visualization. It has been found that the proposed Non Local Non Linear Gaussian Filtering (NL-NLG) filter exhibits the properties of edge preservation, fine detail preservation as well as small structure preservation. At the same time it helps in the removal of speckle also. These properties of structure enhancement, together with speckle removal increase its diagnostic capability.

Ultrasound elastography is an imaging technology which can detect differences in tissue stiffness based on tissue deformation. For successful clinical use in cancer diagnosis and monitoring the method should be robust to sources of decorrelation between ultrasound images. A regularized Dynamic Programming (DP) approach was used for displacement estimation in compressed tissue. In the Analytic Minimization (AM) extension of DP, integer displacements are calculated just for one RF-line, and later propagated laterally throughout the entire image. This makes the seed RF-line very important; faulty seed lines could propagate erroneous displacement values throughout the image resulting in the appearance of false "lesions". In this paper we analyze the robustness of this method in free-hand palpation of laboratory tissue phantoms. We are proposing an update to the algorithm which includes a random search for the most robust seed RF-line. Axial integer displacements are obtained on each random seed line individually with DP optimization. For each random axial RF-line, multiple random values for decorrelation compensation are used in the displacement estimation. The displacement values are then compared and several metrics of stability and consistency are considered. A ranking is established and the line deemed most robust will become the seed line for displacement propagation, while also selecting the most stable value for decorrelation compensation. The random search can be achieved at no additional computational cost in a parallel implementation. The results indicate significant improvement in the robustness of the DP approach, while maintaining real-time computation of strain images.

A finite element (FE)-based simulation model for photoacoustic (PA) has been developed incorporating light propagation, PA signal generation, and sound wave propagation in soft tissues using a commercial FE simulation package, COMSOL Multiphysics. The developed simulation model is evaluated by comparing with other known simulation models such as Monte Carlo method and heat-pressure model. In this in silico simulation, FE model is composed of three parts of 1) homogeneous background soft tissues submerged in water, 2) target tissue inclusion (or PA contrast agents), and 3) short pulsed laser source (pulse length of 5-10 ns). The laser point source is placed right above the tissues submerged in water. This laser source light propagation through the multi-layer tissues using the diffusion equation is compared with Monte Carlo solution. Photoacoustic signal generation by the target tissue inclusion is simulated using bioheat equation for temperature change, and resultant stress and strain. With stress-strain model, the process of the PA signal generation can be simulated further in details step by step to understand and analyze the photothermal properties of the target tissues or PA contrast agents. The created wide-band acoustic pressure (band width > 150 MHz) propagates through the background tissues to the ultrasound detector located at the tissue surface, governed by sound wave equation. Acoustic scattering and absorption in soft tissues also have been considered. Accuracy and computational time of the developed FE-based simulation model of photoacoustics have been quantitatively analyzed.