Institute of Fundamental Technological Research

A new detailed dataset of breast ultrasound scans (BrEaST) containing images of benign and malignant lesions as well as normal tissue examples, is presented. The dataset consists of 256 breast scans collected from 256 patients. Each scan was manually annotated and labeled by a radiologist experienced in breast ultrasound examination. In particular, each tumor was identified in the image using a freehand annotation and labeled according to BIRADS features and lexicon. The histopathological classification of the tumor was also provided for patients who underwent a biopsy.
The BrEaST dataset is the first breast ultrasound dataset containing patient-level labels, image-level annotations, and tumor-level labels with all cases confirmed by follow-up care or core needle biopsy result. To enable research into breast disease detection, tumor segmentation and classification, the BrEaST dataset is made publicly available with the CC-BY 4.0 license.

Introduction: Hemodialysis patients are at higher risk of developing cognitive impairment, but the pattern of affected cognitive domains is still undetermined. Little is also known about the symptoms of depression and anxiety in hemodialysis patients. Methods: In this cross-sectional study, we included 74 consecutive adult patients undergoing hemodialysis. Cognitive functions were assessed using the Addenbrooke Cognitive Test III. In addition, all patients were screened for symptoms of depression and anxiety using the Hospital Anxiety and Depression Scale. Results: The mean age of hemodialysis patients was 65.69 ± 14 years. Among the patients, there were 27% and 31% of patients with mild cognitive impairment and suspected dementia, respectively. In the group of patients with suspected dementia, all cognitive functions had significantly lower values compared to these functions in incognitively unimpaired and mild cognitive impairment patients. The most impaired domain was verbal fluency, which reflects impairments in executive function. Depression and anxiety symptoms were observed in 28% and 22% of patients, respectively. Patients with anxiety symptoms had higher levels of endogenous creatinine, parathyroid hormone, and hemoglobin, as well as decreased creatinine clearance, being younger and less educated. No factors contributing to the occurrence of depressive symptoms were found. Conclusion: Cognitive dysfunction is a significant problem in hemodialysis patients. Our study showed that the prevalence of cognitive impairment and depression and anxiety symptoms in hemodialysis patients was high. The domain of executive functions was most affected. Furthermore, creatinine, parathyroid hormone, hemoglobin levels, creatinine clearance, and education affected the anxiety scale score.

hemodialysis,cognitive impairment,depression,anxiety

Objective: Neoadjuvant chemotherapy (NAC) in breast cancer requires non-invasive methods of monitoring its effects after each dose of drug therapy. The aim is to isolate responding and non-responding tumors prior to surgery in order to increase patient safety and select the optimal medical follow-up. Methods: A new method of monitoring NAC therapy has been proposed. The method is based on image quality indexes (IQI) calculated from ultrasound data obtained from breast tumors and surrounding tissue. Four different tissue regions from the preliminary set of 38 tumors and three data pre-processing techniques are considered. Postoperative histopathology results were used as a benchmark in evaluating the effectiveness of the IQI classification. Results: Out of ten parameters considered, the best results were obtained for the Gray Relational Coefficient. Responding and non-responding tumors were predicted after the first dose of NAC with an area under the receiver operating characteristics curve of 0.88 and 0.75, respectively. When considering subsequent doses of NAC, other IQI parameters also proved usefulness in evaluating NAC therapy. Conclusions: The image quality parameters derived from the ultrasound data are well suited for assessing the effects of NAC therapy, in particular on breast tumors.

Quantitative ultrasound; Image quality; Neoadjuvant chemotherapy; Breast cancer; Treatment response

Introduction. Cognitive impairment (CI) is common in end-stage kidney disease (ESKD), including kidney transplant recipients. Patients with cognitive problems may find it difficult to comply with medical recommendations after kidney transplantation (KT), which can be the cause of many complications, poorer prognosis, and increased hospitalization rates after transplantation. Additionally, some patients after KT may experience depression and anxiety, which are prevalent comorbidities in patients with ESKD. Methods. In this single–center, cross-sectional study, we included 56 consecutive adult patients after KT. Cognitive function were assessed using the Addenbrooke Cognitive Test III (ACE III). In addition, all patients were screened for depression and anxiety using the Hospital Anxiety and Depression Scale (HADS). The impact of immunosuppressive therapy and other disease-related variables on cognitive function were also assessed. Results. A total of 56 KT patients, with a mean age of 50.3 ± 11.7 years, transplanted ≤ 35 months ago were included in the study. The prevalence of CI was 30%. Compared with cognitively unimpaired patients, patients with CI scored significantly lower in all cognitive domains. Furthermore, better cognitive functioning after KT was significantly associated with more years of schooling. We found no significant correlation between CI and age at assessment, duration of dialysis before KT, creatinine levels, creatinine clearance, uric acid levels, hemoglobin levels, comorbid cardiovascular diseases as well as immunosuppressive therapy. In addition, the prevalence of depression and anxiety in screening tests was 12.5% and 27%, respectively, and patients receiving higher daily dose of prednisone had higher HADS scores on both the depression and anxiety subscales (not statistically significant). Downloaded from http://karger.com/kbr/article-pdf/doi/10.1159/000533755/3991154/000533755.pdf by guest on 05 September 2023 Discussion/Conclusion. Cognitive disorders is a relevant issue in kidney transplant recipients. There might be many factors, both before and after KT, that have a negative impact on cognition. Therefore, further research is needed to increase knowledge about the course and profile of cognitive function after KT.

cognitive impairment,kidney transplantation,immunosuppressive therapy,ACE III test,HADS

Background: Cognitive impairment (CI) in patients with chronic kidney disease, including those treated with renal replacement therapy, is a growing problem worldwide. Objectives: The study aimed to assess the prevalence of CI and associated factors in patients undergoing peritoneal dialysis (PD). Methods: In this cross-sectional study, 18 consecutive patients with PD therapy and 15 controls were evaluated for CI using the Addenbrooke’s Cognitive Examination III (ACE III) test. Results: The prevalence of CI was 33% in patients and 27% in the control group and was not statistically significant. A higher prevalence of CI was found in subjects aged ≥65 years old than in those <65 years old (p = 0.02), but only in the control group. The prevalence of CI in PD patients over and under 65 years of age did not differ statistically significantly (p = 0.12). Memory and verbal fluency were the most affected cognitive domain in PD patients with CI (p = 0.00, p = 0.04, respectively). There was a significant correlation between higher educated PD patients and the ACE III test results. The duration of dialysis did not affect the results of the cognitive screening test. Conclusions: CI is a growing problem in the course of chronic kidney disease and dialysis therapy. It seems that cognitive problems may occur in patients undergoing PD at a younger age than in the general population with particularly affected memory and verbal fluency. Higher educated patients score better on the cognitive screening test.

Cognitive impairment,Chronic kidney disease,Peritoneal dialysis,Addenbrooke’s Cognitive Examination III test,Screening test

In an interesting article previously published in Data in Brief [Dataset of breast ultrasound images" by W. Al-Dhabyani, M. Gomaa, H. Khaled & A. Fahmy, Data in Brief, 2020, 28, 104863], the authors presented a dataset of breast ultrasound images containing lesions. As of April 22, 2023, this study has garnered significant attention from researchers, as evident by its 298 citations in Scopus data. This is unsurprising considering that the study presents one of the few publicly available datasets on breast ultrasound images, as well as binary masks highlighting the lesions. When implementing various aspects of explainable AI, we verify the correctness of the input data at every stage, especially when using various data sources. In an attempt to use this dataset for research, we did some exploration and identified some inconsistencies that could have a significant impact on the results of the studies utilizing them. As the role of tumor detection is indisputable we feel obliged to point attention to some aspects that need to be kept in mind while using this database in order to receive reliable and good quality results.

The objective of this paper is an experimental study of the most crucial parameters of the received acoustic signals (e.g. signal-to-noise ratio (SNR), side-lobes level (SLL), axial resolution) obtained as a result of si-multaneous emission of mutually orthogonal Golay complementary sequences (MOGCS) to demonstrate their feasibility of being used in ultrasound diagnostics. Application of the MOGCS in ultrasound measurements allows the image reconstruction time to be shortened without decreasing the resulting quality of econstructed images in comparison with regular complementary Golay coded sequences (CGCS). In this paper two sets of 16-bits long MOGCS were implemented in the Verasonics VantageTM (Verasonics Inc., Kirkland, WA, USA) scanner. Ultrasound data were generated using a perfect reflector, a custom-made nylon wire phantom and tissue mimicking phantom. Parameters of the detected MOGCS echoes like SNR, SLL and axial resolution were determined and compared to that of the standard CGCS and the short two-sine cycles pulse. It was evidenced that applying MOGCS did not compromise the parameters of the separated and compressed echoes in compa-rison to the other types of transmitted signal – the CGCS and the short pulse. Concretely, both the MOGCS and CGCS yield similar SNR increase in comparison to the short pulse. Almost similar values of the axial reso-lution estimated at the full width at the half maximum level for all types of the transmitted signals were also obtained. At the same time, using the MOGCS the data acquisition speed can be increased twice in comparison with the CGCS signal.

coded excitation; mutually orthogonal Golay codes; synthetic aperture; ultrasound imaging

Background and objective: This paper is focused on the analysis of a method of estimation of the absorption and scattering coefficients of nonhomogeneous two layered structures in time resolved near infrared spectroscopy using method based on cumulative distributions of time of flight of photons. Methods: The research is based on the analysis of the superposition of cumulative distributions of time of flight of photons. This approach allows for detailed analysis of small variations in characteristics of time of flight of photons caused by an electromagnetic propagation in highly scattering non-homogeneous media. The method presented, based on the variation of statistical minimum distance estimation, is compared to the method of standard curve fitting. It is analyzed by fitting the results obtained from Monte-Carlo simulations of light propagation in the turbid medium to the data from the simulated measurements. Results: The analysis is carried out for a vast range of optical properties of two layered medium in reflectance geometry. Conclusions: The method allows the estimation of the optical parameters despite the noise in the measured signal, with higher accuracy and generally with smaller number of error function evaluations.

optical properties, approximation, light propagation, time of flight of photons, Monte-Carlo simulations, cumulative distributions

Acoustical Driving Forces (ADF), induced by propagating waves in a homogeneous and inhomogeneous lossy fluid (suspension), are determined and compared depending on the concentration of suspended particles. Using integral equations of the scattering theory, the single particle (inclusion) ADF was calculated as the integral of the flux of the momentum density tensor components over the heterogeneity surface. The possibility of negative ADF was indicated. Originally derived, the total ADF acting on inclusions only, stochastically distributed in ambient fluid, was determined as a function of its concentration. The formula for the relative increase in ADF, resulting from increased concentration was derived. Numerical ADF calculations are presented. In experiments the streaming velocities in a blood-mimicking starch suspension (2 μm radius) in water and Bracco BR14 contrast agent (SF6 gas capsules, 1 μm radius) were measured as the function of different inclusions concentration. The source of the streaming and ADF was a plane 2 mm diameter 20 MHz ultrasonic transducer. Velocity was estimated from the averaged Doppler spectrum obtained from originally developed pulsed Doppler flowmeter. Numerical calculations of the theoretically derived formula showed very good agreement with the experimental results.

streaming suspension, scattering, acoustical driving force, Doppler measurements, contrast agents

The computing performance optimization of the Short-Lag Spatial Coherence (SLSC) method applied to ultrasound data processing is presented. The method is based on the theory that signals from adjacent receivers are correlated, drawing on a simplified conclusion of the van Cittert-Zernike theorem. It has been proven that it can be successfully used in ultrasound data reconstruction with despeckling. Former works have shown that the SLSC method in its original form has two main drawbacks: time-consuming processing and low contrast in the area near the transceivers. In this study, we introduce a method that allows to overcome both of these drawbacks. The presented approach removes the dependency on distance (the "lag" parameter value) between signals used to calculate correlations. The approach has been tested by comparing results obtained with the original SLSC algorithm on data acquired from tissue phantoms. The modified method proposed here leads to constant complexity, thus execution time is independent of the lag parameter value, instead of the linear complexity. The presented approach increases computation speed over 10 times in comparison to the base SLSC algorithm for a typical lag parameter value. The approach also improves the output image quality in shallow areas and does not decrease quality in deeper areas.

short lag spatial coherence, synthetic aperture, algorithm optimization, parallel processing

A method of suppression of grating lobes is presented, analyzed, and verified. The method is based on creating a Virtual Receiving Subaperture (VRS) by adding virtual transducer elements not existing in the physical layout of the receiver. The VRS channels are filled with data based on signals from real channels. The analytical model of the synthetic aperture imaging system's impulse response is presented to describe the properties of the VRS. The model shows a reduction of the receiving grating lobes' amplitude (with a comparison to the main lobe’s amplitude) by a magnitude equal to the number of receiving transducer elements. It is shown that effective properties of the entire system with a VRS are similar to a system with a pitch in the receiving aperture that is twice as small. The numerical calculations of the impulse response show a doubling of the signal to noise ratio, which results in a reduction of the receiving grating lobes. For experimental validation, the generalized Plane Wave Imaging with and without the VRS is compared with a basic synthetic transmit aperture (STA) imaging. The experiment confirmed that the use of a VRS allows for visualizat ion of the objects in a medium in which they are not imaged without a VRS or are visualized with a lower contrast. The reduction of grating lobes attained using the proposed method is at the level of 15dB in the visualization of the superficial cyst.

grating lobes, image quality, synthetic aperture, virtual subaperture

Two different barite ore (barium sulfate BaSO4) specimens from different localizations were tested and described in this paper. Analysis of the microstructure was performed on polished sections, and on thin sections using X-ray microtomography (micro-CT), and optical microscopy (MO). Microtomography allowed obtaining three-dimensional images of the barite aggregate specimens. In the tomograms, the spatial distribution of the other polluting phases, empty space as well as cracks, pores, and voids – that exceeded ten micrometers of diameter-were possible to visualize. Also, the micro-CT allowed distinguishing between minerals of different density, like SiO2 and BaSO4. Images obtained and analyzed on thin sections with various methods using the optical microscopy in transmitted light delivered additional information on the aggregate microstructure, i.e. allow for estimation of the different kinds of inclusions (like the different density of the minerals) in the investigated specimens. Above methods, which were used in the tests, completed each another in order to supply a set of information on inclusions' distribution and to present the important differences of the barite aggregate specimens microstructure.

barite ore, barite aggregate, microstructure, optical microscopy, thin sections analysis, X-ray tomography

The nEUROPt protocol is one of two new protocols developed within the European project nEUROPt to characterize the performances of time-domain systems for optical imaging of the brain. It was applied in joint measurement campaigns to compare the various instruments and to assess the impact of technical improvements. This protocol addresses the characteristic of optical brain imaging to detect, localize, and quantify absorption changes in the brain. It was implemented with two types of inhomogeneous liquid phantoms based on Intralipid and India ink with well-defined optical properties. First, small black inclusions were used to mimic localized changes of the absorption coefficient. The position of the inclusions was varied in depth and lateral direction to investigate contrast and spatial resolution. Second, two-layered liquid phantoms with variable absorption coefficients were employed to study the quantification of layer-wide changes and, in particular, to determine depth selectivity, i.e., the ratio of sensitivities for deep and superficial absorption changes. We introduce the tests of the nEUROPt protocol and present examples of results obtained with different instruments and methods of data analysis. This protocol could be a useful step toward performance tests for future standards in diffuse optical imaging.

A multi-center study has been set up to accurately characterize the optical properties of diffusive liquid phantoms based on Intralipid and India ink at near-infrared (NIR) wavelengths. Nine research laboratories from six countries adopting different measurement techniques, instrumental set-ups, and data analysis methods determined at their best the optical properties and relative uncertainties of diffusive dilutions prepared with common samples of the two compounds. By exploiting a suitable statistical model, comprehensive reference values at three NIR wavelengths for the intrinsic absorption coefficient of India ink and the intrinsic reduced scattering coefficient of Intralipid-20% were determined with an uncertainty of about 2% or better, depending on the wavelength considered, and 1%, respectively. Even if in this study we focused on particular batches of India ink and Intralipid, the reference values determined here represent a solid and useful starting point for preparing diffusive liquid phantoms with accurately defined optical properties. Furthermore, due to the ready availability, low cost, long-term stability and batch-to-batch reproducibility of these compounds, they provide a unique fundamental tool for the calibration and performance assessment of diffuse optical spectroscopy instrumentation intended to be used in laboratory or clinical environment. Finally, the collaborative work presented here demonstrates that the accuracy level attained in this work for optical properties of diffusive phantoms is reliable.

Optical technique based on diffuse reflectance measurement combined with indocyanine green (ICG) bolus tracking is extensively tested as a method for clinical assessment of brain perfusion in adults at the bedside. Methodology of multiwavelength and time-resolved detection of fluorescence light excited in the ICG is presented and advantages of measurements at multiple wavelengths are discussed. Measurements were carried out: 1. on a physical homogeneous phantom to study the concentration dependence of the fluorescence signal, 2. on the phantom to simulate the dynamic inflow of ICG at different depths, and 3. in vivo on surface of the human head. Pattern of inflow and washout of ICG in the head of healthy volunteers after intravenous injection of the dye was observed for the first time with time-resolved instrumentation at multiple emission wavelengths. The multiwavelength detection of fluorescence signal confirms that at longer emission wavelengths, probability of reabsorption of the fluorescence light by the dye itself is reduced. Considering different light penetration depths at different wavelengths, and the pronounced reabsorption at longer wavelengths, the time-resolved multiwavelength technique may be useful in signal decomposition, leading to evaluation of extra- and intracerebral components of the measured signals

indocyanine green bolus, near-infrared spectroscopy, fluorescence, time-resolved spectra, multiwavelength detection

A time-gated intensified CCD camera was applied for time-resolved imaging of light penetrating in an optically turbid medium. Spatial distributions of light penetration probability in the plane perpendicular to the axes of the source and the detector were determined at different source positions. Furthermore, visiting probability profiles of diffuse reflectance measurement were obtained by the convolution of the light penetration distributions recorded at different source positions. Experiments were carried out on homogeneous phantoms, more realistic two-layered tissue phantoms based on the human skull filled with Intralipid–ink solution and on cadavers. It was noted that the photons visiting probability profiles depend strongly on the source–detector separation, the delay between the laser pulse and the photons collection window and the complex tissue composition of the human head

It was reported that time-resolved reflectance measurements carried out during inflow and washout of an optical contrast agent may provide information on the blood supply to the brain cortex of human adults. It was also shown that a measurement of fluorescence excited in the dye circulating in the brain is feasible. Unfortunately, patterns of time-resolved fluorescence signals observed during in vivo measurements are difficult to interpret. The aim of this study was to analyze the influence of several factors on the fluorescence signals measured during in vivo experiments. A laboratory instrument for recording the distributions of arrival of fluorescence photons was constructed and optimized for measurements on humans. Monte Carlo simulations and laboratory measurements on liquid phantoms as well as in vivo measurements on healthy volunteers were carried out. An influence of source–detector separation, position of the source–detector pair on the head, as well as a dose of the injected indocyanine green (ICG) on the fluorescence signals were studied in detail. It was shown that even for a small dose of ICG (0.025 mg kg−1) the time-resolved signals can be successfully detected on the surface of the head. Strong influence of the studied factors on the fluorescence signals was observed. It was also noted that the changes in moments of distributions of arrival times of fluorescence photons depend on the anatomical structure of the tissues located between the source and the detector.

The near infrared spectroscopy may be implemented using various optoelectronic techniques, however, most of them do notallow to carry out measurements at short source−detector separation. We propose a method, based on time−gated intensifiedCCD camera, which allows for contactless measurements and can be carried out at short source−detector separation. This technique was tested on a phantom with absorbing inclusions buried in an optically turbid medium which mimics localchanges in oxygenation of the brain tissue

time−resolved NIRS, time−gated intensified CCD camera, short source−detector separation

Manual image segmentations are naturally subject to inaccuracies related to systematic errors (due to the tools used, eye-hand coordination, etc.). This was noted earlier when a simplified accuracy scale was proposed [1]. This scale arbitrarily divides a given range of values of the Kappa measurement parameter into classes: almost perfect (>0.80), substantial (0.61 - 0.80), moderate (0.41 - 0.60), fair (0.21 - 0.40), slight (0.00 - 0.21) and poor (< 0.00). However, the determination of threshold values between classes is not entirely clear and seems to be application-dependent. This is particularly important for images in which the tumor-normal tissue boundary can be very indistinct, as is observed in ultrasound imaging of the most common cancer in women - breast cancer [2]. In machine learning, there is an ongoing contest over the values of performance indicators obtained from new neural network architecture without accounting for any ground truth bias. This raises the question of what relevance, from a segmentation quality point of view, a gain at the level of single percentages has [3] if the references have much greater uncertainty. So far, research on this topic has been limited. The relationship between the segmentations of breast tumors on ultrasound images provided by three radiologists and those obtained using deep learning model has been studied in [4]. Unfortunately, the indicated segmentation contour sometimes varied widely in all three cases. A cursory analysis by multiple physicians, which focused only on the Kappa coefficient in the context of physicians’ BI-RADS category assignments, was conducted in the [5]. In this article, we present a preliminary analysis of the accuracy of experts’ manually prepared binary breast cancer masks on ultrasound images and their impact on performance metrics commonly used in machine learning. In addition, we examined how tumor type or BI-RADS category [6] affects the accuracy of tumor contouring.

Standard classification methods based on hand-crafted morphological and texture features have achieved good performance in breast mass differentiation in ultrasound (US).
In comparison to deep neural networks, commonly perceived as ‘black-box’ models, classical techniques are based on features that have well-understood medical and physical interpretation. However, classifiers based on morphological features commonly
underperform in the presence of the shadowing artifact and ill-defined mass borders, while texture based classifiers may fail when the US image is too noisy. Therefore, in practice it would be beneficial to select the classification method based on the appearance of the particular US image. In this work, we develop a deep meta-network that can automatically process input breast mass US images and recommend whether to apply the shape or
texture based classifier for the breast mass differentiation. Our preliminary results demonstrate that meta-learning techniques can be used to improve the performance of the standard classifiers based on handcrafted features. With the proposed meta-learning based approach, we achieved the area under the receiver operating characteristic curve of 0.95 and accuracy of 0.91.

breast mass classification, deep learning, meta-learning, morphological features, texture features

Understanding the relationship between acoustic properties of breast lesions and resulting ultrasound images may contribute to an earlier and more accurate diagnosis of the most common cancer in women. In addition to in vitro studies, in silico tumor models can provide a lot of crucial information due to the possibility of precise determination of the influence of changes in tissue structure on the resulting ultrasound echoes. The purpose was to develop the numerical phantom of the breast with the tumor for a reliable simulation of ultrasound images. In modeling the tissue structures of the breast, the VICTRE phantom, developed by the FDA for the simulation of X-ray mammography, was used. The numerical ultrasound model of breast cancer allows the simulation of ultrasound signals and images. It could be used to interpret, validate and develop new ultrasound methods for cancer diagnosis

breast tumor, numerical phantom, ultrasound imaging

Local ultrasonic tissue ablation is induced by a rapid (<3s) rise in temperature in a small ellipsoidal volume (about 13mm3) inside the tissue to a cytotoxic level when exposed to a high-intensity focused ultrasound (HIFU) beam. The aim of this study was to develop a numerical tool to predict the location and extent of a necrotic lesion formed locally inside the ex vivo tissue as a result of exposure to a single or multiple HIFU beam, ensuring the efficacy and safety of destroying solid tumors. The proposed tool was based on modelling the non-linear propagation of acoustic waves and heat transfer in heterogeneous media using the k-wave toolbox. The wave propagation equations were solved for two-layer (water/tissue) media. The source of the acoustic waves was a spherical bowl-shaped transducer with a resonance frequency of 1.08 MHz. The distribution of heat sources was determined from the calculated acoustic pressure distribution in the HIFU beam. The obtained temperature distributions during heating and cooling allowed calculation of the thermal dose and prediction of the extent of the necrotic lesion. The obtained results of numerical simulations were compared with the experimental data from previous studies. The mean difference between the calculated and measured length or diameter of a single exposure induced necrotic lesion was approximately 1 mm. In the case of a necrotic lesion induced by multiple exposures, the mean difference between the measured and calculated cross-sectional area of the planned necrotic lesion covered with necrosis was approximately 11.2 %.

HIFU, modelling, numerical simulations, treatment planning, ex vivo experiments, necrotic lesions, thermal ablation, experimental verification

A new toolbox for the simulation of acoustic wave fields is described. The toolbox, USim, is designed to make an acoustic modeling of ultrasound propagation in tissues reliable and fast. The forward simulations of the wave field are based on the Born-Neumann single scattering approximation of the solution of Sturm-Liouville equation. The toolbox allows simulating the ultrasound wave propagation in non-homogeneous media containing finite size scatterers similar to those existing in a real tissues. The approach of calculations conducted in Fourier space increases the efficiency and allows taking into account the absorption and density phenomena in a simple and correct way.

acoustic propagation, numerical simulations, fourier domain

Our goal is to develop a complete ultrasound platform based on real-time SAFT (Synthetic Aperture Focusing Technique) GPU processing. We are planning to integrate all the ultrasound modules and processing resources (GPU) in a single rack enclosure with the PCIe switch fabric backplane. The first developed module (RX64) provides acquisition and streaming of 64 ultrasound channels. We implemented and benchmarked data streaming from the RX64 to the GPU memory and the SAFT image reconstruction on the GPU. A high system performance was achieved using hardware assisted direct memory transfers and pipelined processing workflow. The complete system throughput, including 128 channel data transfer at 16kS per line and low-resolution 256×256 pixel image SAFT reconstruction on a single Nvidia K5000 GPU, reached 450 fps. The obtained results proved the feasibility of the ultrasound real-time imaging system with GPU SAFT processing.

ultrasonic imaging, synthetic aperture, GPGPU, FPGA

Acoustical Driving Forces (ADF), induced by propagating waves in a homogeneous and inhomogeneous lossy fluid (suspension), are determined and compared depending on the concentration of suspended particles. Using integral equations of the scattering theory, the single particle (inclusion) ADF was calculated as the integral of the flux of the momentum density tensor components over the heterogeneity surface. The possibility of negative ADF was indicated. Originally derived, the total ADF acting on inclusions only, stochastically distributed in ambient fluid, was determined as a function of its concentration. The formula for the relative increase in ADF, resulting from increased concentration was derived. Numerical ADF calculations are presented. In experiments the streaming velocities in a blood-mimicking starch suspension (2 mu m radius) in water and Bracco BR14 contrast agent (SF6 gas capsules, 1 mu m radius) were measured as the function of different inclusions concentration. The source of the streaming and ADF was a plane 2 mm diameter 20 MHz ultrasonic transducer. Velocity was estimated from the averaged Doppler spectrum obtained from originally developed pulsed Doppler flowmeter. Numerical calculations of the theoretically derived formula showed very good agreement with the experimental results.

A new 128 channel parallel acquisition module for the Ultrasonix SonixTouch ultrasound scanner was developed. Although the module provides similar functionality to the original SonixDAQ system, it presents new possibilities of real-time data streaming and processing on GPU, thanks to a fast PCIe communication interface. Direct access and processing of pre-beamformed channel data with fully programmable transmit schemes enables the research implementation of new advanced imaging modalities (eg. plane wave imaging, vector Doppler, shear wave elastography). The presented RX-DAQ system is enriched with a GPU software framework, for Python and Matlab, enabling the integration of user processing functions.

ultrasonic imaging, pre-beamformed data, real-time processing, GPU, FPGA