This PDF file contains the front matter associated with SPIE Proceedings Volume 6920, including the Title Page, Copyright information, Table of Contents, Introduction (if any), and the Conference Committee listing.

Various methods are used in ultrasound beamforming to increase signal-to-noise ratio (SNR) and improve spatial resolution. SNR is typically improved by exploiting coherence in the RF channel data, for example summing channel data after applying focal delays in the delay-and-sum (DAS) beamformer, and summing channel data after applying a per-channel matched filter for the spatial matched filter beamformer[1]. Inverse filter methods are capable of improving spatial resolution at the cost of SNR [2],[3], or can trade resolution for SNR using a regularization parameter, but in general are very computationally intensive due to the large RF data sets used. We propose a post-processing method operating on post-summed but pre-envelope detected beamformed image data that can improve the pixel SNR and spatial resolution of any beamformer with low computational cost. This is achieved by forming a new pixel for each point in the image as a linear combination of the surrounding beamformed pixels. The weights for each pixel are calculated in advance using a quadratically constrained least squares method to reduce PSF energy outside the mainlobe and noise energy. Simulations indicate that this method can increase cystic contrast by up to 20dB without any cost in SNR, and can increase pixel SNR can by up 16dB without affecting contrast. Alternatively, simultaneous gains in contrast and SNR can be achieved. Experimental results show smaller performance improvements yet validate the feasibility of this technique.

Digital beamforming has been widely used in modern medical ultrasound instruments. Flexibility is the key advantage of a digital beamformer over the traditional analog approach. Unlike analog delay lines, digital delay can be programmed to implement new ways of beam shaping and beam steering without hardware modification. Digital beamformers can also be focused dynamically by tracking the depth and focusing the receive beam as the depth increases. By constantly updating an element weight table, a digital beamformer can dynamically increase aperture size with depth to maintain constant lateral resolution and reduce sidelobe noise. Because ultrasound digital beamformers have high I/O bandwidth and processing requirements, traditionally they have been implemented using ASICs or FPGAs that are costly both in time and in money. This paper introduces a sample implementation of a digital beamformer that is programmed in software on a Massively Parallel Processor Array (MPPA). The system consists of a host PC and a PCI Express-based beamformer accelerator with an Ambric Am2045 MPPA chip and 512 Mbytes of external memory. The Am2045 has 336 asynchronous RISCDSP processors that communicate through a configurable structure of channels, using a self-synchronizing communication protocol.

Software implementation of a medical ultrasound imaging system using commercial DSPs (Digital Signal Processor) has advantages over FPGA- or ASIC-based system in development cost and time. The authors have developed a full software-based ultrasound scanner consisting of a typical analog front-end block and a DSP system. In this work, we present efficient methods for software realization of an echo processor to perform all the ultrasound signal processing functions following the receive beamforming. For implementation with a single TMS320C6416 DSP, the most computationally demanding functions such as dynamic filtering, quadrature demodulation, decimation, magnitude calculation, and log compression are implemented using modified algorithms and structures optimized to best match the DSP architecture for fast computation. The DSC (digital scan converter) is realized with an LUT for generating memory addresses and interpolation coefficients for each display point. The LUT table is stored in a single external SDRAM so that the internal DSP memory can be fully utilized by the DSP core to maximize the processing speed. The possible memory stall that can be caused by the external memory access is removed by properly employing the enhanced direct memory access channels. Experimental results show that the proposed implementation can support up to 4 kHz PRF (pulse repetition frequency) when the input data rate is 40 MHz.

In this study, we investigated the characteristics of the ultrasound reflective image obtained by a CMOS sensor array coated with piezoelectric material (PE-CMOS). The laboratory projection-reflection ultrasound prototype consists of five major components: an unfocused ultrasound transducer, an acoustic beam splitter, an acoustic compound lens, a PE-CMOS ultrasound sensing array (Model I400, Imperium Inc. Silver Spring, MD), and a readout circuit system. The prototype can image strong reflective materials such as bone and metal. We found this projection-reflection ultrasound prototype is able to reveal hairline bone fractures with and without intact skin and tissue. When compared, the image generated from a conventional B-scan ultrasound on the same bone fracture is less observable. When it is observable with the B-scan system, the fracture or crack on the surface only show one single spot of echo due to its scan geometry. The corresponding image produced from the projection-reflection ultrasound system shows a bright blooming strip on the image clearly indicating the fracture on the surface of the solid material. Speckles of the bone structure are also observed in the new ultrasound prototype. A theoretical analysis is provided to link the signals as well as speckles detected in both systems.

Many signal processing issues in ultrasonic imaging can be viewed as attempts to focus signal energy while preserving the diagnostic information they contain. We have been developing a task-based ideal-observer approach to signal processing with the goal of better understanding the factors that influence the transfer of diagnostic information and improving signal processing algorithms for optimal transfer. We treat the scattering medium as a Gaussian random field with non-uniform variance that encodes the properties necessary for accurate task performance. Using measured pointspread functions for a given system we propagate the scattering statistics through to various stages of the acquisition process along with acquisition noise. In this work we focus on the role of beamforming in this process. We consider the efficiency of information transfer by analyzing the ideal observer acting on individual receive elements and then considering different strategies for preserving diagnostic information in beamformed echo signals. Optimal beamforming strategies suggested by the analysis are approximated by applying spatial filtering techniques to fixedfocus echo data. These results are compared with a standard delay-and-sum beamformer.

Ultrasound reflection imaging is a promising imaging modality for detecting small, early-stage breast cancers. Properly accounting for ultrasound scattering from heterogeneities within the breast is essential for high-resolution and high-quality ultrasound breast imaging. We develop a globally optimized Fourier finite-difference method for ultrasound reflectivity image reconstruction. It utilizes an optimized solution of acoustic-wave equation and a heterogeneous sound-speed distribution of the breast obtained from tomography to reconstruct ultrasound reflectivity images. The method contains a finite-difference term in addition to the split-step Fourier implementation, and minimizes ultrasound phase errors during wavefield inward continuation while maintaining the advantage of high computational efficiency. The accuracy analysis indicates that the optimized method is much more accurate than the split-step Fourier method. The computational efficiency of the optimized method is one to two orders of magnitude faster than time-reversal imaging using a finite-difference time-domain wave-equation scheme. Our new optimized method can accurately handle ultrasound scattering from breast heterogeneities during reflectivity image reconstruction. Our numerical imaging examples demonstrate that the optimized method has the potential to produce high-quality and high-resolution ultrasound reflectivity images in combination with a reliable ultrasound sound-speed tomography method.

In this paper, a discrete model representing the pulse-tissue interaction in the medical ultrasound scanning and imaging process is developed. The model is based on discretizing the acoustical wave equation and is in terms of convolution between the input ultrasound pulses and the tissue mass density variation. Such a model can provide a useful means for ultrasound echo signal processing and imaging. Most existing models used for ultrasound imaging are based on frequency domain transform. A disadvantage of the frequency domain transform is that it is only applicable to shift-invariant models. Thus it has ignored the shift-variant nature of the original acoustic wave equation where the tissue compressibility and mass density distributions are spatial-variant factors. The discretized frequency domain model also obscures the compressibility and mass density representations of the tissue, which may mislead the physical understanding and interpretation of the image obtained. Moreover, only the classical frequency domain filtering methods have been applied to the frequency domain model for acquiring some tissue information from the scattered echo signals. These methods are non-parametric and require a prior knowledge of frequency spectra of the transmitted pulses. Our proposed model technique will lead to discrete, multidimensional, shift-variant and parametric difference or convolution equations with the transmitted pulse pressure as the input, the measurement data of the echo signals as the output, and functions of the tissue compressibility and mass density distributions as shift-variant parameters that can be readily identified from input-output measurements. The proposed model represents the entire multiple scattering process, and hence overcomes the key limitation in the current ultrasound imaging methods.

To improve clinical breast imaging, a new ultrasound tomography imaging device (CURE) has been built at the Karmanos Cancer Institute. The ring array of the CURE device records ultrasound transmitted and reflected ultrasound signals simultaneously. We develop a bent-ray tomography algorithm for reconstructing the sound-speed distribution of the breast using time-of-flights of transmitted signals. We study the capability of the algorithm using a breast phantom dataset and over 190 patients' data. Examples are presented to demonstrate the sound-speed reconstructions for different breast types from fatty to dense on the BI-RADS categories 1-4. Our reconstructions show that the mean sound-speed value increases from fatty to dense breasts: 1440.8 m/ s (fatty), 1451.9 m/ s (scattered), 1473.2 m/ s(heterogeneous), and 1505.25 m/ s (dense). This is an important clinical implication of our reconstruction. The mean sound speed can be used for breast density analysis. In addition, the sound-speed reconstruction, in combination with attenuation and reflectivity images, has the potential to improve breast-cancer diagnostic imaging. The breast is not compressed and does not move during the ultrasound scan using the CURE device, stacking 2D slices of ultrasound sound-speed tomography images forms a 3D volumetric view of the whole breast. The 3D image can also be projected into a 2-D "ultrasound mammogram" to visually mimic X-ray mammogram without breast compression and ionizing radiation.

The point spread function (PSF) of an imaging system may be used as measure for the imaging quality. The PSF usually depends on position and an several other system parameters. Our current 3D imaging system for ultrasound computer tomography consists of a rotatable cylinder with approx. 2000 ultrasound transducers. 3D images are reconstructed by means of synthetic aperture focusing technique (SAFT) using all available emitter-receiver-combinations. No analytical solution exists for determining the spatially varying PSF for arbitrary placement of the transducers. This work derives a new numerical approach for the approximation of the 3D PSF for arbitrary transducer geometries including the beam pattern of the ultrasound transducers, a directional point scatterer model, damping of the breast and arbitrary pulse shapes. As an exemplary application the spatially varying 3D PSF of the current cylindrical geometry is analyzed under idealized conditions (point sources, no damping, and isotropic scattering) and compared to non-idealized results of the PSF analysis. The results show the necessity to take the system specific parameters into account for a realistic prognosis of 3D imaging performance.

Using medical implants to wirelessly report physiological data is a technique that is rapidly growing. Ultrasound is well-suited for implants -- it requires little power and this form of radiated energy has no ill effects on the body. We report here on techniques we have developed in our experience gained in implanting over a dozen Doppler ultrasound flow-measuring implants in dogs. The goal of our implantable device is to measure flow in an arterial graft. To accomplish this, we place a Doppler transducer in the wall of a graft and an implant unit under the skin that energizes the 20 MHz Doppler transducer system, either when started by external command or by internal timetable. The implant records the digitized Doppler real and imaginary channels and transmits the data to a nearby portable computer for storage and evaluation. After outlining the overall operation of the system, we will concentrate on three areas of implant design where special techniques are required: ensuring safety, including biocompatibility to prevent the body from reacting to its invasion; powering the device, including minimizing energy used so that a small battery can provide long-life; and transmitting the data obtained.

Image gating is related to image modalities that involve quasi-periodic moving organs. Therefore, during intravascular ultrasound (IVUS) examination, there is cardiac movement interference. In this paper, we aim to obtain IVUS gated images based on the images themselves. This would allow the reconstruction of 3D coronaries with temporal accuracy for any cardiac phase, which is an advantage over the ECG-gated acquisition that shows a single one. It is also important for retrospective studies, as in existing IVUS databases there are no additional reference signals (ECG). From the images, we calculated signals based on average intensity (AI), and, from consecutive frames, average intensity difference (AID), cross-correlation coefficient (CC) and mutual information (MI). The process includes a wavelet-based filter step and ascendant zero-cross detection in order to obtain the phase information. Firstly, we tested 90 simulated sequences with 1025 frames each. Our method was able to achieve more than 95.0% of true positives and less than 2.3% of false positives ratio, for all signals. Afterwards, we tested in a real examination, with 897 frames and ECG as gold-standard. We achieved 97.4% of true positives (CC and MI), and 2.5% of false positives. For future works, methodology should be tested in wider range of IVUS examinations.

This paper evaluates the quality of segmentation achieved by a level set evolution strategy call Tunneling Descent. Level sets often evolve and become stationary at the nearest local minimum of an energy function. A comparison of the local level set minimum with a global minimum is important for many applications. This is especially true of ultrasound segmentation where ultrasound speckle can introduce many local minima which trap the level set. In this paper, we compare the quality of the level set segmentation with the quality of segmentation achieved by (1) simulated annealing (with three different cooling schedules), and (2) random sampling, and (3) three experts (manual segmentation). Simulated annealing and random sampling offer global minimization. In this paper, the quality of the segmentation is compared for 21 clinically-obtained images. The comparison is carried out using two performance measures: the amount by which the global minimizers can further decrease the level set energy, and the contour distance between the segmentations themselves. The results show that level set segmentation is within one ultrasound resolution cell of the global minimum. The results also show that the level set segmentation is quite close to manual segmentation.

Analyzing the artery mechanics is a crucial issue because of its close relationship with several cardiovascular risk factors, such as hypertension and diabetes. Moreover, most of the work can be carried out by analyzing image sequences obtained with ultrasounds, that is with a non-invasive technique which allows a real-time visualization of the observed structures. For this reason, therefore, an accurate temporal localization of the main vessel interfaces becomes a central task for which the manual approach should be avoided since such a method is rather unreliable and time consuming. Real-time automatic systems are advantageously used to automatically locate the arterial interfaces. The automatic measurement reduces the inter/intra-observer variability with respect to the manual measurement which unavoidably depends on the experience of the operator. The real-time visual feedback, moreover, guides physicians when looking for the best position of the ultrasound probe, thus increasing the global robustness of the system. The automatic system which we developed is a stand-alone video processing system which acquires the analog video signal from the ultrasound equipment, performs all the measurements and shows the results in real-time. The localization algorithm of the artery tunics is based on a new mathematical operator (the first order absolute moment) and on a pattern recognition approach. Various clinical applications have been developed on board and validated through a comparison with gold-standard techniques: the assessment of intima-media thickness, the arterial distension, the flow-mediated dilation and the pulse wave velocity. With this paper, the results obtained on clinical trials are presented.

Color Doppler ultrasound imaging is a powerful non-invasive diagnostic tool for many clinical applications that involve examining the anatomy and hemodynamics of human blood vessels. These clinical applications include cardio-vascular diseases, obstetrics, and abdominal diseases. Since its commercial introduction in the early eighties, color Doppler ultrasound imaging has been used mainly as a qualitative tool with very little attempts to quantify its images. Many imaging artifacts hinder the quantification of the color Doppler images, the most important of which is the aliasing artifact that distorts the blood flow velocities measured by the color Doppler technique. In this work we will address the color Doppler aliasing problem and present a recovery methodology for the true flow velocities from the aliased ones. The problem is formulated as a 2D phase-unwrapping problem, which is a well-defined problem with solid theoretical foundations for other imaging domains, including synthetic aperture radar and magnetic resonance imaging. This paper documents the need for a phase unwrapping algorithm for use in color Doppler ultrasound image analysis. It describes a new phase-unwrapping algorithm that relies on the recently developed cutline detection approaches. The algorithm is novel in its use of heuristic information provided by the ultrasound imaging modality to guide the phase unwrapping process. Experiments have been performed on both in-vitro flow-phantom data and in-vivo human blood flow data. Both data types were acquired under a controlled acquisition protocol developed to minimize the distortion of the color Doppler data and hence to simplify the phase-unwrapping task. In addition to the qualitative assessment of the results, a quantitative assessment approach was developed to measure the success of the results. The results of our new algorithm have been compared on ultrasound data to those from other well-known algorithms, and it outperforms all of them.

Intravascular ultrasound (IVUS) has been proven a reliable imaging modality that is widely employed in cardiac interventional procedures. It can provide morphologic as well as pathologic information on the occluded plaques in the coronary arteries. In this paper, we present a new technique using wavelet packet analysis that differentiates between blood and non-blood regions on the IVUS images. We utilized the multi-channel texture segmentation algorithm based on the discrete wavelet packet frames (DWPF). A k-mean clustering algorithm was deployed to partition the extracted textural features into blood and non-blood in an unsupervised fashion. Finally, the geometric and statistical information of the segmented regions was used to estimate the closest set of pixels to the lumen border and a spline curve was fitted to the set. The presented algorithm may be helpful in delineating the lumen border automatically and more reliably prior to the process of plaque characterization, especially with 40 MHz transducers, where appearance of the red blood cells renders the border detection more challenging, even manually. Experimental results are shown and they are quantitatively compared with manually traced borders by an expert. It is concluded that our two dimensional (2-D) algorithm, which is independent of the cardiac and catheter motions performs well in both in-vivo and in-vitro cases.

Administering epidural anesthesia can be a difficult procedure, especially for inexperienced physicians. The use of ultrasound imaging can help by showing the location of the key surrounding structures: the ligamentum flavum and the lamina of the vertebrae. The anatomical depiction of the interface between ligamentum flavum and epidural space is currently limited by speckle and anisotropic reflection. Previous work on phantoms showed that adaptive spatial compounding with non-rigid registration can improve the depiction of these features. This paper describes the development of an updated compounding algorithm and results from a clinical study. Average-based compounding may obscure anisotropic reflectors that only appear at certain beam angles, so a new median-based compounding technique is developed. In order to reduce the computational cost of the registration process, a linear prediction algorithm is used to reduce the search space for registration. The algorithms are tested on 20 human subjects. Comparisons are made among the reference image plus combinations of different compounding methods, warping and linear prediction. The gradient of the bone surfaces, the Laplacian of the ligamentum flavum, and the SNR and CNR are used to quantitatively assess the visibility of the features in the processed images. The results show a significant improvement in quality when median-based compounding with warping is used to align the set of beam-steered images and combine them. The improvement of the features makes detection of the epidural space easier.

The shapes of malignant breast tumors are more complex than the benign lesions due to their nature of infiltration into surrounding tissues. We investigated the efficacy of shape features and presented a method using polygon shape complexity to improve the discrimination of benign and malignant breast lesions on ultrasound. First, 63 lesions (32 benign and 31 malignant) were segmented by K-way normalized cut with the priori rules on the ultrasound images. Then, the shape measures were computed from the automatically extracted lesion contours. A polygon shape complexity measure (SCM) was introduced to characterize the complexity of breast lesion contour, which was calculated from the polygonal model of lesion contour. Three new statistical parameters were derived from the local integral invariant signatures to quantify the local property of the lesion contour. Receiver operating characteristic (ROC) analysis was carried on to evaluate the performance of each individual shape feature. SCM outperformed the other shape measures, the area under ROC curve (AUC) of SCM was 0.91, and the sensitivity of SCM could reach 0.97 with the specificity 0.66. The measures of shape feature and margin feature were combined in a linear discriminant classifier. The resubstitution and leave-one-out AUC of the linear discriminant classifier were 0.94 and 0.92, respectively. The distinguishing ability of SCM showed that it could be a useful index for the clinical diagnosis and computer-aided diagnosis to reduce the number of unnecessary biopsies.

For freehand ultrasound systems, a calibration method is necessary to locate the position and orientation of a 2D B-mode ultrasound image plane with respect to a position sensor attached to the transducer. In addition, the acquisition time discrepancy between the position measurements and the image frames has the be computed. We developed a new method that adresses both of these problems, based on the fact that a freehand ultrasound system establishes consistent 3D data of an arbitrary object. Two angulated sweeps of any object containing well visible structures are recorded, each at a different orientation. A non-linear optimization strategy maximizes the similarity of 2D ultrasound images from one sweep to reconstructions computed from the other sweep. No designated phantom is required for this calibration. The process can be performed in vivo on the patient. We evaluated our method using freehand acquisitions on both a phantom and the human liver. The accuracy of the approach was validated using a 3D ultrasound probe as a known reference geometry.

Spatial compounding has been used in ultrasonic imaging for suppressing speckle noise. The technique generally involves electronically steering the ultrasonic beams. In this paper, we present a spatial compounding approach where the component image is acquired by mechanically rotating the probe element. A linear transducer array is rotated about an axis in the plane of the image. The goal is to avoid the problems associated with the electronic beam steering at a large angle such as decrease in the effective aperture size, grating lobe effect, and decrease in transducer sensitivity caused by obliquity factor. In the computation of the ultrasound image, we need the values of the axis of rotation and angular position of the transducer array. However, the construction of the rotation mechanism and the control system accompanies the inevitable uncertainties in these values. These parameter errors result in the target position error, and the consequence is the blurry compounded image. We present the spatial compounding for rotating linear probe in the presence of parameter error using image registration. The effect of the uncertainty in the mechanical parameters was compensated by registering the wire target images before spatial compounding. An efficient registration algorithm was developed to compute the transformation matrix required for the registration. The component images were registered by the transformation matrix before spatial compounding and the effect of the parameter errors were removed.

Most of the techniques for generating and detecting ultrasonic Lamb waves (e.g. angle-beam piezoelectric transducers, micro-electro mechanical systems (MEMS), comb and interdigital transducers, phased array transducers, and piezoceramic transducers) require a firm physical contact with the measured objects. For objects with highly irregular surfaces such as bones, it will be very difficult to produce a good contact. Thus, a non-contact Lamb wave measurement technique, the scanning laser vibrometry, is proposed in this paper to examine a bovine cortical tibia in vitro. The ultrasonic Lamb waves used had the center frequency of 84KHz. The waves were generated using a planar transducer which was coupled with a cone-shaped resonant vibrator. Only the fundamental modes of a₀ and s₀ were expected to occur. 2-Dimensional images of the Lamb waves traveling in the bone were recorded. The scan results represent out-of-plane vibration of the surface of the bone. Lamb wave modes were verified with further post-processing analyses. In time-domain, time-history prediction of the modes is fitted onto the original detected signal as to confirm their common rising time for each mode. A frequency-domain method, i.e. wavelet analysis, is also employed to define the traveling modes and their group velocity. The expected modes can be clearly defined at the center frequency. Additionally, what seemed to be a new mode, a₁, was generated and detected at the higher frequency of the responses.

We report and discuss clinical breast imaging results obtained with operator independent ultrasound tomography. A series of breast exams are carried out using a recently upgraded clinical prototype designed and built on the principles of ultrasound tomography. The in-vivo performance of the prototype is assessed by imaging patients at the Karmanos Cancer Institute. Our techniques successfully demonstrate in-vivo tomographic imaging of breast architecture in both reflection and transmission imaging modes. These initial results indicate that operator-independent whole-breast imaging and the detection of cancerous breast masses are feasible using ultrasound tomography techniques. This approach has the potential to provide a low cost, non-invasive, and non-ionizing means of evaluating breast masses. Future work will concentrate on extending these results to larger trials.

In obstetrics, antenatal ultrasound assessment of placental morphology comprises an important part of the estimation of fetal health. Ultrasound analysis of the placenta may reveal abnormalities such as placental calcification and infarcts. Current methods of quantification of these abnormalities are subjective and involve a grading system of Grannum stages I-III. The aim of this project is to develop a software tool that quantifies semi-automatically placental ultrasound images and facilitates the assessment of placental morphology. We have developed a 2D ultrasound imaging software tool that allows the obstetrician or sonographer to define the placental region of interest. A secondary reference map is created for use in our quantification algorithm. Using a slider technique the user can easily define an upper threshold based on high intensity for calcification classification and a lower threshold to define infarction regions based on low intensity within the defined region of interest. The percentage of the placental area that is calcified and also the percentage of infarction is calculated and this is the basis of our new metric. Ultrasound images of abnormal and normal placentas have been acquired to aid our software development. A full clinical prospective evaluation is currently being performed and we are currently applying this technology to the three-dimensional ultrasound domain. We have developed a novel software-based technique for calculating the extent of placental calcification and infarction, providing a new metric in this field. Our new metric may provide a more accurate measurement of placental calcification and infarction than current techniques.

Women with high mammographic breast density are at 4- to 6-fold increased risk of developing breast cancer compared to women with fatty breasts. However, current breast density estimations rely on mammography, which cannot provide accurate volumetric breast representation. Therefore, we explored two techniques of breast density evaluation via ultrasound tomography. A sample of 93 patients was imaged with our clinical prototype; each dataset contained 45-75 tomograms ranging from near the chest wall through the nipple. Whole breast acoustic velocity was determined by creating image stacks and evaluating the sound speed frequency distribution. Ultrasound percent density (USPD) was determined by segmenting high sound speed areas from each tomogram using k-means clustering, integrating over the entire breast, and dividing by total breast area. Both techniques were independently evaluated using two mammographic density measures: (1) qualitative, determined by a radiologist's visual assessment using BI-RADS Categories, and (2) quantitative, via semi-automatic segmentation to calculate mammographic percent density (MPD) for craniocaudal and medio-lateral oblique mammograms. ~140 m/s difference in acoustic velocity was observed between fatty and dense BI-RADS Categories. Increased sound speed was found with increased BI-RADS Category and quantitative MPD. Furthermore, strong positive associations between USPD, BI-RADS Category, and calculated MPD were observed. These results confirm that utilizing sound speed, both for whole-breast evaluation and segmenting locally, can be implemented to evaluate breast density.

Current ultrasound methods for measuring myocardial strain are often limited to measurements in one or two dimensions. Spatio-temporal elastic registration of 3D cardiac ultrasound data can however be used to estimate the 3D motion and full 3D strain tensor. In this work, the spatio-temporal elastic registration method was validated for both non-scanconverted and scanconverted images. This was done using simulated 3D pyramidal ultrasound data sets based on a thick-walled deforming ellipsoid and an adapted convolution model. A B-spline based frame-to-frame elastic registration method was applied to both the scanconverted and non-scanconverded data sets and the accuracy of the resulting deformation fields was quantified. The mean accuracy of the estimated displacement was very similar for the scanconverted and non-scanconverted data sets and thus, it was shown that 3D elastic registration to estimate the cardiac deformation from ultrasound images can be performed on non-scanconverted images, but that avoiding of the scanconversion step does not significantly improve the results of the displacement estimation.

By developing a real-time visualization system, pulsatile tissue-motion caused by artery pulsation of blood flow has been visualized continuously from a video stream of ultrasonogram in brightness mode. The system concurrently executes the three processes: (1) capturing an input B-mode video stream (640×480 pixels/frame, 30 fps) into a ring buffer of 256 frames, (2) detecting intensity and phase of pulsatile tissue-motion at each pixel from a heartbeat-frequency component in Fourier transform of a series of pixel value through the latest 64 frames as a function of time, and (3) generating an output video-stream of pulsatile-phase image, in which the motion phase is superimposed as color gradation on an input video-stream when the motion intensity exceeds a proper threshold. By optimizing the visualization software with the streaming SIMD extensions, the pulsatile-phase image has been continuously updated at more than 10 fps, which was enough to observe pulsatile tissue-motion in real time. Compared to the retrospective technique, the real-time visualization had clear advantages not only in enabling bedside observation and quick snapshot of pulsatile tissue-motion but also in giving useful feedback to probe handling for avoiding unwanted motion-artifacts, which may strongly assist pediatricians in bedside diagnosis of ischemic diseases.

We present and validate image-based speckle-tracking calipers for quantification of tissue deformation and rotation in dynamic cardiovascular phantom models. Lagrangian strain was computed from the change in distance between caliper regions-of-interest (ROIs) positioned within the wall of a pulsatile phantom and compared with reference measurements derived from cardiac CT imaging. In a torsion phantom, rotational tissue excursion in a 2D plane was estimated and compared with reference values from CT-scan data. Tissue deformation and rotation measurements correlated well with their respective reference measurements. Our algorithm is capable of estimating strain and rotation from distinct tissue regions without requiring explicit cardiac border detection, a step which can be especially challenging in patients with poor acoustic windows.

Intravascular Ultrasound (IVUS) palpography is a techniques that depicts the distribution of the mechanical strain over the luminal surface of coronary arteries. It utilizes conventional radiofrequency (RF) signals acquired at two different levels of a compressional load. The signals are cross-correlated to obtain the microscopic tissue displacements, which can be directly translated into local strain of the vessel wall. However, (apparent) tissue motion and nonuniform deformation of the vessel wall due to catheter jolting and rotation reduce signal correlation and result in void strain estimates. Implications of probe motion were studied on the tissue-mimicking phantom. The measured circumferential tissue displacement and level of the speckle decorrelation amounted to 12° and 0.58 for the catheter displacement of 800 μm, respectively. To compensate for the motion artifacts in IVUS palpography, a novel method, based on the feature-based scale-space Optical Flow (OF) was employed. The computed OF vector field quantifies the amount of the local tissue misalignment in consecutive frames. Subsequently, the extracted motion pattern is used to realign the signals prior to the cross-correlation analysis, reducing signal decorrelation and increasing the number of valid strain estimates. The advantage of applying the motion compensation algorithms was demonstrated in a mid-scale validation study on 14 in-vivo pullbacks. Both methods substantially increase the number of valid strain estimates in the partial and compounded palpograms. A mean relative improvement amounts to 28% and 14%, respectively. Implementation of motion compensation method increase the diagnostic value of IVUS palpography.

Elastography, an ultrasound modality based on the relation between tissue strain and its mechanical properties, has a strong potential in the diagnosis and prognosis of tumors. For instance, tissue affected by breast and prostate cancer undergoes a change in its elastic properties. These changes can be measured using ultrasound signals. The standard way to visualize the elastic properties of tissues in elastography is the representation of the axial strain. Other approaches investigate the information contained in shear strain elastograms, vorticity or the representation of the full strain tensor. In this paper, we propose to represent the elastic behaviour of tissues through the visualization of the Strain Index, related with the trace of the strain tensor. Based on the mathematical interpretation of the strain tensor, this novel parameter is equivalent to the sum of the eigenvalues of the strain tensor, and constitutes a measure of the total amount of strain of the soft tissue. In order to show the potential of this visualization approach, a tissue-mimicking phantom was modeled as a 10x10x5 cm region containing a centered 10mm cylindrical inclusion three times stiffer than the surrounding material, and its elastic behavior was simulated using finite elements software. Synthetic pre- and post-compression (1.25%) B-mode images were computer-generated with ultrasound simulator. Results show that the visualization of the tensor trace significantly improves the representation and detection of inclusions, and can help add insight in the detection of different types of tumors.

Changes in tissue stiffness correlate with pathological phenomena that can aid the diagnosis of several diseases such as breast and prostate cancer. Ultrasound elastography measures the elastic properties of soft tissues using ultrasound signals. The standard way to estimate the displacement field from which researchers obtain the strain in elastography is the time-domain cross-correlation estimator (TDE). Optical flow (OF) methods have been also characterized and their use keeps increasing. We introduce in this paper the use of a Modified Demons Algorithm (MDA) to estimate the displacement field and we compare it with OF. A least-squares strain estimator (LSE) is applied to estimate the strain from the displacement. The input for the algorithm comes from the ultrasound scanner standard video output; therefore, its clinical implementation is immediate. To test the algorithm, a tissuemimicking phantom was modeled as a 10x10x5 cm region containing a centered 10mm cylindrical inclusion three times stiffer than the surrounding material, and its elastic behavior was simulated using COMSOL Multiphysics 3.2 software. Synthetic pre- and post-compression (1.25%) B-mode images were computer generated using FIELD II ultrasound simulator. Afterward, the algorithm was tested with a commercial CIRS breast elastography phantom, applying a 2% freehand compression. Axial displacement fields and strain figures are presented and in the case of the synthetic one compared to the ground truth given by the FE software. Although other researchers have used registration methods for elastography, as far as we know, they have not been used as stand alone but together with elastic modulus reconstruction or FE which iteratively varies material properties to improve registration.

We present a software-based ultrasound beamformer to build a fully software-based ultrasound scanner which performs real-time delay-sum beamforming using fractional delay filters using ADSP-TS201 DPSs (Analog Device Inc.). Receive dynamic focusing generally requires fast transfer of a large amount of data for inter-channel summation and for delay control. The DSPs are connected in pipelined network architecture without a glue logic using the DPS's parallel ports, which allows the connection of unlimited DSPs. Each DSP has a small input FIFO which takes as input the data samples from each ADC and can take delay values either from a memory (to use pre-calculated delay values) or an external FPGA (for real-time delay calculation) via its LVDS channel. Two fractional delay beamformer (FDBF) schemes are implemented on the DSP system. Each scheme is programmed in assembly code optimized for speed; instruction level parallelism is secured to maximally utilize the four execution units of each DSP, pipeline scheduling is employed to avoid pipeline stall, and instruction reordering techniques are used to prevent memory contention while preserving the program semantics. It is found that dynamic focusing is carried out faster when delay filtering is performed prior to interchannel summation, whereas hardware implementation of the FDBF favors performing delay filtering after interchannel summation. The frame rate achievable with 16 DSPs is up to 28Hz when the sampling rate is 40MHz, the view depth is 20cm, the number of scanline is 128, and the number of channel is 64.

At Forschungszentrum Karlsruhe an Ultrasound Computer Tomography system USCT) is under development for early breast cancer detection. To detect morphological indicators in sub-millimeter resolution, the visualization is based on a SAFT algorithm (synthetic aperture focusing technique). The current 3D demonstrator system consists of approx. 2000 transducers, which are arranged in layers on a cylinder of 18 cm diameter and 15 cm height. With 3.5 millions of acquired raw data sets and up to one billion voxels for an image, a reconstruction may last up to months. In this work a performance optimized SAFT algorithm is developed. The used software environment is MathWorks' MATLAB. Several approaches were analyzed: a plain M-code (MATLAB's native language), an optimized M-code, a C-code implementation, and a low-level assembler implementation. The fastest found solution uses an SIMD enhanced assembler code wrapped in the C-interface of MATLAB. Additionally a 10% speed up is gained by reducing the function call overhead. The overall speed up is more than one order of magnitude. The resulting computational efficiency is near the theoretical optimum. The reconstruction time is significantly reduced without losing MATLAB's comfortable development environment.

In such applications as fast 3D imaging with 2D arrays and point-of-care imaging with an ultra portable devices, periodic sparse arrays(PSA) can be efficiently used to increase the effective aperture size with less number of active elements than the conventional method. Generally, PSA can be represented as sub-arrays distributed uniformly in P -element intervals, each with L consecutive elements, where L < P. Since the continuous wave beam pattern in the far-field is given by Fourier transform of aperture function, the beam pattern of PSA is a multiplication of beam patterns of the upsampled dense array by the ratio of P and L -elements sub-array. A recent method to design a PSA pair provides analytically the values of P and L for transmit and receive arrays to eliminate the dominant grating lobes, which occur at the same position on both transmit and receive. In this work, we present a method to design a PSA pair with improved performance by further suppressing the residual grating lobes of PSA. It can be accomplished by properly shading amplitude of the transmit and receive sparse arrays. This shading window function is also obtained by signal analysis of aperture functions. The beam patterns of various PSA pairs based on the proposed design method are evaluated through computer simulations. The simulation results show that the residual grating lobes are reduced by about 10dB more in all cases. Consequently, our method can be used to improve the performance of beam pattern or enhance the periodicity of sparse array.

Photoacoustic imaging is used to obtain a range of three-dimensional images representing tumor neovascularization over a 10-day period after subcutaneous inoculation of pancreatic tumor cells in a rat. The images are reconstructed from data measured with a double-ring photoacoustic detector. The ultrasound data originates from the optical absorption by hemoglobin of 14 ns laser pulses at a wavelength of 1064 nm. Three-dimensional data is obtained by using two dimensional linear scanning. Scanning and motion artifacts are reduced using a correction method. The data is used to visualize the development of the individual blood vessels around the growing tumor, blood concentration changes inside the tumor and growth in depth of the neovascularized region. The three-dimensional vasculature reconstruction is created using VTK, which enables us to create a composition of the vasculature on day seven, eight and ten and to interactively measure tumor growth in the near future.

Photoacoustic imaging is an upcoming medical imaging modality with the potential of imaging both optical and acoustic properties of objects. We present a measurement system and outline reconstruction methods to image both speed of sound and acoustic attenuation distributions of an object using only pulsed light excitation. These acoustic properties can be used in a subsequent step to improve the image quality of the optical absorption distribution. A passive element, which is a high absorbing material with a small cross-section such as a carbon fiber, is introduced between the light beam and the object. This passive element acts as a photoacoustic source and measurements are obtained by allowing the generated acoustic signal to propagate through the object. From these measurements we can extract measures of line integrals over the acoustic property distribution for both the speed of sound and the acoustic attenuation. Reconstruction of the acoustic property distributions then comes down to the inversion of a linear system relating the obtained projection measurements to the acoustic property distributions. We show the results of applying our approach on phantom objects. Satisfactory results are obtained for both the reconstruction of speed of sound and the acoustic attenuation.

A novel clinical prototype, CURE (Computed Ultrasound Risk Evaluation), is used to collect breast tissue image data of patients with either benign or malignant masses. Three types of images, reflection, sound speed and attenuation, are generated from the raw data using tomographic reconstruction algorithms. Each type of image, usually presented as a gray scale image, maps different characteristics of the breast tissue. This study is focused on fusing all three types of images to create true color (RGB) images by assigning a different primary color to each type of image. The resulting fused images display multiple tissue characteristics that can be viewed simultaneously. Preliminary results indicate that it may be possible to characterize breast masses on the basis of viewing the superimposed information. Such a methodology has the potential to dramatically reduce the time required to view all the acquired data and to make a clinical assessment. Since the color scale can be quantified, it may also be possible to segment such images in order to isolate the regions of interest and to ultimately allow automated methods for mass detection and characterization.

Ultrasound attenuation parameters of breast masses are closely related to their types and pathological states, therefore, it is essential to reliably estimate attenuation parameters for quantitative breast tissue characterization. We study the applicability of three different attenuation tomography methods for ultrasound breast imaging using a ring transducer array. The first method uses the amplitude decays of signals transmitted through the breast to reconstruct attenuation coefficients. The second method employs the spectral ratios between the pulse propagating through the breast and that through water to obtain attenuation parameters. The third method makes use of the complex energy ratios estimated using the amplitude envelopes of transmitted signals. We use in vitro and in vivo breast data acquired with a clinical ultrasound breast imaging system (CURE) to compare these tomography methods. Our results show that the amplitude decay method yields attenuation coefficients with more artifacts than the other two methods. There is bias and variability in the estimated attenuation using the spectral ratio due to its sensitivity to different temporal band-widths and signal-to-noise-ratios of the data. The method based on the complex signal energy ratio is more robust than the other two methods and yields images with fewer artifacts.

The theory on microbubbles clearly indicates a relation between the ambient pressure and the acoustic behavior of the bubble. The purpose of this study was to optimize the sensitivity of ambient pressure measurements, using the subharmonic component, through microbubble response simulations. The behaviour of two different contrast agents was investigated as a function of driving pulse and ambient overpressure, p_ov. Simulations of Levovist using a rectangular driving pulse show an almost linear reduction in the subharmonic component as p_ov is increased. For a 20 cycles driving pulse, a reduction of 4.6 dB is observed when changing p_ov from 0 to 25 kPa. Increasing the pulse duration makes the reduction even more clear. For a pulse with 64 cycles, the reduction is 9.9 dB. This simulation is in good correspondence with measurement results presented by Shi et al. 1999, who found a linear reduction of 9.6 dB. Further simulations of Levovist show that also the shape and the acoustic pressure of the driving pulse are very important factors. The best pressure sensitivity of Levovist was found to be 0.88 dB/kPa. For Sonazoid, a sensitivity of 0.71 dB/kPa has been found, although the reduction is not completely linear as a function of the ambient pressure.

An efficient method for separating the harmonic component (2f0) from the fundamental component (f0) using harmonic quadrature demodulation is presented. In the proposed method, the focused ultrasound signal is mixed with cosine and sine signal waveforms of harmonic frequency 2f0 to produce the inphase and quadrature components, respectively. The quadrature component is Hilbert-transformed and then added to the inphase component. This process cancels out both the high and low frequency components of the mixed fundamental signal and the high frequency component of the mixed harmonic signal, leaving only the envelope of the harmonic signal at the base band. This signal is then fed to a low-pass filter to remove out of band noise. In summary, this method can extract the harmonic signal after a single transmit-receive event even when there exists frequency overlap between the f0 and 2f0 components. Hence, the proposed method is superior to the pulse inversion method which requires twice as many transmit-receive cycles as well as the conventional filtering method which has a bandwidth limitation. Therefore, one can find the proposed method useful not only for tissue harmonic imaging but also for contrast agent imaging in applications where high frame rate or low motion artifact is important. The proposed method is verified by both the analytic and computer simulation studies. For a stationary target, the difference between the estimated harmonic signals by the proposed and the pulse inversion methods is within 0.1%.

The capability of sonoelastography to detect lesions based on elasticity contrast can be applied to monitor the creation of thermally ablated lesion. Currently, segmentation of lesions depicted in sonoelastographic images is performed manually which can be a time consuming process and prone to significant intra- and inter-observer variability. This work presents a semi-automated segmentation algorithm for sonoelastographic data. The user starts by planting a seed in the perceived center of the lesion. Fast marching methods use this information to create an initial estimate of the lesion. Subsequently, level set methods refine its final shape by attaching the segmented contour to edges in the image while maintaining smoothness. The algorithm is applied to in vivo sonoelastographic images from twenty five thermal ablated lesions created in porcine livers. The estimated area is compared to results from manual segmentation and gross pathology images. Results show that the algorithm outperforms manual segmentation in accuracy, inter- and intra-observer variability. The processing time per image is significantly reduced.