Ultrasound Transmission Tomography Research Articles

Low frequency 3D transmission ultrasound tomography: technical details and clinical implications

A novel 3D ultrasound tomographic (3D UT) method (called volography) that creates a speed of sound (SOS) map and a reflection modality that is co-registered are reviewed and shown to be artifact free even in the presence of high contrast and thus shown to be applicable for breast, orthopedic and pediatric clinical use cases. The 3D UT images are almost isotropic with mm resolution and the reflection image is compounded over 360 degrees to create sub-mm resolution in plane. MethodsThe physics of ultrasound scattering requires 3D modeling and the concomitant high computational cost is ameliorated with a bespoke algorithm (paraxial approximation – discussed here) and Nvidia GPUs. The resulting reconstruction times are tabulated for clinical relevance. The resulting SOS map is used to create a refraction corrected reflection image at ∼3.6 MHz center frequency. The transmission data are highly redundant, collected over 360 degrees and at 2 mm levels by true matrix receiver arrays yielding 3D data.The high resolution SOS and attenuation maps and reflection images are used in a segmentation algorithm that optimally utilizes this information to segment out glandular, ductal, connective tissue, fat and skin. These volumes are used to estimate breast density, an important correlate to cancer. ResultsMultiple SOS images of breast, knee and segmentations of breast glandular and ductal tissue are shown. Spearman rho is calculated between our volumetric breast density estimates and Volpara™ from mammograms, as 0.9332. Multiple timing results are shown and indicate the variability of the reconstruction times with breast size and type but are ∼30 minutes for average size breast. The timing results with the 3D algorithm indicate ∼60 minute reconstruction times for pediatrics with two Nvidia GPUs. Characteristic variations of the glandular and ductal volumes over time are shown. The SOS from QT images are compared with literature values.The results of a multi-reader multi-case (MRMC) study are shown that compares the 3D UT with full field digital mammography and resulted in an average increase in ROC AUC of 10%. Orthopedic (knee) 3D UT images compared with MRI indicate regions of zero signal in the MRI are clearly displayed in the QT image.Explicit representation of the acoustic field is shown, indicating its 3D nature. An image of in vivo breast with the chest muscle is shown and speed of sound agreement with literature values are tabulated. Reference is made to a recently published paper validating pediatric imaging. ConclusionsThe high Spearman rho indicates a monotonic (not necessarily linear) relation between our method and industry gold standard Volpara™ density. The acoustic field verifies the need for 3D modeling. The MRMC study, the orthopedic images, breast density study, and references, all indicate the clinical utility of the SOS and reflection images. The QT image of the knee shows its ability to monitor tissue the MRI cannot. The included references and images herein indicate the proof of concept for 3D UT as a viable and valuable clinical adjunct in pediatric and orthopedic situations in addition to the breast imaging.

Regularization of the Solution for Noisy Data Using the FOCUSS Method in Transmission Ultrasound Tomography

Regularization of the Solution for Noisy Data Using the FOCUSS Method in Transmission Ultrasound Tomography

Energy Reduction with Super-Resolution Convolutional Neural Network for Ultrasound Tomography

This study addresses the issue of energy optimization by investigating solutions for the reduction of energy consumption in the diagnostics and monitoring of technological processes. The implementation of advanced process control is identified as a key approach for achieving energy savings and improving product quality, process efficiency, and production flexibility. The goal of this research is to develop a cost-effective system with a minimal number of ultrasound sensors, thus reducing the energy consumption of the overall system. To accomplish this, a novel method for obtaining high-resolution reconstruction in transmission ultrasound tomography (t-UST) is proposed. The method involves utilizing a convolutional neural network to take low-resolution measurements as input and output high-resolution sinograms that are used for tomography image reconstruction. This approach allows for the construction of a super-resolution sinogram by utilizing information hidden in the low-resolution measurement. The model is trained on simulation data and validated on real measurement data. The results of this technique demonstrate significant improvement compared to state-of-the-art methods. The study also highlights that UST measurements contain more information than previously thought, and this hidden information can be extracted and utilized with the use of machine learning techniques to further improve image quality and object recognition.

Internal imaging of concrete fracture based on elastic waves and ultrasound computed tomography

The condition assessment of concrete structures belongs to the greatest challenges of non-destructive testing. Monitoring the fracture process of concrete and detecting cracks at the earliest possible stage is a vital aspect to ensure the safety of civil engineering objects. The use of ultrasound tomography enables imaging the internal structure of a tested element. This study aims at the visualization of fracture damage in concrete cubes. The tests are performed on samples made of plain concrete and concrete with fibres. The main contribution of this work is the study of the application of ultrasound transmission tomography to imaging cracks in concrete prisms before and after mechanical degradation in a wedge splitting test. A novel method of determination of the time-of-flight of a wave propagating from a transmitter to a receiver is introduced. The effectiveness of the imaging of fracture damage obtained using ultrasound tomography is proved by X-ray micro-computed tomography.

APPLICATION OF FINITE DIFFERENCE METHOD FOR MEASUREMENT SIMULATION IN ULTRASOUND TRANSMISSION TOMOGRAPHY

In this work, we present a computer simulation model that generates the propagation of sound waves to solve a forward problem in ultrasound transmission tomography. The simulator can be used to create data sets used in the supervised learning process. A solution to the "free-space" boundary problem was proposed, and the memory consumption was significantly optimized from O(n2) to O(n). The given method of simulating wave scattering enables the control of the noise extinction time within the tomographic probe and the permeability of the sound wave. The presented version of the script simulates the classic variant of a circular probe with evenly distributed sensors around the circumference.

Ultrasound transmission and reflection tomography for nondestructive testing using experimental data

The possibility of reconstructing the velocity structure of inspected objects with a high spatial resolution and high sensitivity in ultrasonic tomographic nondestructive testing within the framework of a wave model has been demonstrated in a real experiment. In this study, a scheme of a tomographic experiment with rotation is proposed, which provides sounding of an inspected object from multiple sides. A tomographic scheme of the experiment with linear antenna transducer arrays operating at a frequency of ∼5 MHz was used. The experiment was conducted on dedicated samples including inserts with different sound propagation velocities. It was shown that the velocity structure and the boundaries of inserts can be reconstructed in the transmission and the reflection schemes. The reconstruction of the velocity structure was formulated as a nonlinear coefficient inverse problem for a scalar wave equation. Efficient iterative methods for its solution on a supercomputer were developed using direct formulas to compute the gradient of the residual functional between the computed and experimentally measured wave field at the detectors. Nonlinearity of the inverse problem of ultrasound tomography leads to multiple local minima of the residual functional. A two-stage iterative method was used for velocity reconstruction. The transmission scheme enables a spatial resolution of approximately 1 mm with a velocity contrast of 2%.

Ultrasound transmission tomography-guided heating with nanoparticles

Nanoparticles can be used in numerous therapeutic procedures, including controlled drug delivery and release, thermal therapy, and photo- and sonodynamic therapy. However, such approaches remain limited due to difficulties associated with accurately controlling their therapeutic efficiency and localized consequences. Thus, we propose the use of ultrasound transmission tomography (UTT) measurements following ultrasonic heating when using nanomaterials as mediators. We test various nanomaterials doped to agar tissue-mimicking phantoms to study how they affect the UTT imaging through improving the contrast. Simultaneously, we investigate the suitability of these mediators in relation to the process of ultrasonic heating under the guidance of UTT. The results show that UTT is sensitive to the presence of magnetic nanoparticle-based nanomaterials and induced temperature rises. The combination of an imaging modality based on generally safe and well-known ultrasound-based imaging and the use of nanomaterials as mediators represents our proposal for a new theranostic approach.

Ultrasound and Photoacoustic Imaging of Breast Cancer: Clinical Systems, Challenges, and Future Outlook.

Presently, breast cancer diagnostic methods are dominated by mammography. Although drawbacks of mammography are present including ionizing radiation and patient discomfort, not many alternatives are available. Ultrasound (US) is another method used in the diagnosis of breast cancer, commonly performed on women with dense breasts or in differentiating cysts from solid tumors. Handheld ultrasound (HHUS) and automated breast ultrasound (ABUS) are presently used to generate reflection images which do not contain quantitative information about the tissue. This limitation leads to a subjective interpretation from the sonographer. To rectify the subjective nature of ultrasound, ultrasound tomography (UST) systems have been developed to acquire both reflection and transmission UST (TUST) images. This allows for quantitative assessment of tissue sound speed (SS) and acoustic attenuation which can be used to evaluate the stiffness of the lesions. Another imaging modality being used to detect breast cancer is photoacoustic tomography (PAT). Utilizing much of the same hardware as ultrasound tomography, PAT receives acoustic waves generated from tissue chromophores that are optically excited by a high energy pulsed laser. This allows the user to ideally produce chromophore concentration maps or extract other tissue parameters through spectroscopic PAT. Here, several systems in the area of TUST and PAT are discussed along with their advantages and disadvantages in breast cancer diagnosis. This overview of available systems can provide a landscape of possible intersections and future refinements in cancer diagnosis.

Breast Transmission Ultrasound Tomography Based on Capacitive Micromachined Ultrasonic Transducer Linear Arrays

Ultrasound computed tomography (USCT) has become a useful means of breast cancer imaging detection. In this paper, a novel breast ultrasound tomography system based on capacitive micromachined ultrasonic transducer (CMUT) linear arrays is built. Implementation method of parallel beam filtered back-projection algorithm in the background of USCT is derived. The feasibility of breast ultrasound tomography system based on CMUT and the applicability of image reconstruction algorithm are preliminarily proved by simulation experiment and breast phantom experiment. Sound speed image and sound impedance image are fused to obtain the breast ultrasound tomography image with edge information and structure information simultaneously. According to experimental results, size reconstruction deviation of simulated tumor in the breast phantom is about 14%, which is reduced by 57.14% after multimodal image fusion ultimately. The research results in this study provide the theoretical basis and technical support for the application of CMUT in the field of medical imaging.

Ultrasound tomography reconstruction algorithm using two opposite rotatable linear arrays for breast cancer diagnosis

This article presents a new ultrasound transmission tomography reconstruction algorithm based on a isometric fan-shaped beam along the straight trajectory for an original breast ultrasound imaging system with the cylindrical motion of opposite linear arrays. The ultrasound computed tomography system and measurement scheme are described in detail. The reconstruction algorithm is derived. The numerical breast phantom model is built, including eight structures representing the adipose tissue, glandular tissue, cysts, fibroadenomas, cancer, and calcifications. Using one array as a transmitter and the other one as a receiver, the attenuation distribution in a medium interposed between them is reconstructed. However, limited angle tomography is usually plagued by artifacts along the depth of the image that cause shape distortion to be ellipses, which had an impact on the accurate judgment of the size and shape. B-mode ultrasound images are used as prior information to aid in improving the image quality of limited aperture reconstructions. Simulation results show that the number, location, size, and shape of cancer, cyst, fibroadenoma, and calcification in the numerical breast phantom are reconstructed. Moreover, the quantitative analysis of reconstructed images demonstrates that the reconstruction performance of the region of interest has been greatly improved, which verifies the feasibility of the algorithm using two opposite linear arrays. The reconstruction images are produced by the designed ultrasound tomography reconstruction algorithm, allowing the assessment of the morphology, orientation, internal structure, and margins of lesions in the breast tissue. The ability to create good attenuation images using the cylindrical motion of opposite linear arrays allows reconstructing the three-dimensional image for breast cancer detection and characterization studies.

Principal component analysis of measured data for ultrasound transmission tomography

In this paper, the new version of imaging algorithm for Ultrasound Transmission Tomography was presented. This algorithm was comprehensively tested with both synthetic and real measurement data. Different configuration of an internal objects was considered. In order to improve the quality of imaging the input data were treated by Principal Component Analysis. The proposed algorithm proved its usefulness and superiority over classical imaging algorithms.

Ultrasound transmission tomography image reconstruction with a fully convolutional neural network

Image reconstruction of ultrasound computed tomography based on the wave equation is able to show much more structural details than simpler ray-based image reconstruction methods. However, to invert the wave-based forward model is computationally demanding. To address this problem, we develop an efficient fully learned image reconstruction method based on a convolutional neural network. The image is reconstructed via one forward propagation of the network given input sensor data, which is much faster than the reconstruction using conventional iterative optimization methods. To transform the ultrasound measured data in the sensor domain into the reconstructed image in the image domain, we apply multiple down-scaling and up-scaling convolutional units to efficiently increase the number of hidden layers with a large receptive and projective field that can cover all elements in inputs and outputs, respectively. For dataset generation, a paraxial approximation forward model is used to simulate ultrasound measurement data. The neural network is trained with a dataset derived from natural images in ImageNet and tested with a dataset derived from medical images in OA-Breast Phantom dataset. Test results show the superior efficiency of the proposed neural network to other reconstruction algorithms including popular neural networks. When compared with conventional iterative optimization algorithms, our neural network can reconstruct a 110 × 86 image more than 20 times faster on a CPU and 1000 times faster on a GPU with comparable image quality and is also more robust to noise.

Full wave 3D inverse scattering transmission ultrasound tomography in the presence of high contrast

We present here a quantitative ultrasound tomographic method yielding a sub-mm resolution, quantitative 3D representation of tissue characteristics in the presence of high contrast media. This result is a generalization of previous work where high impedance contrast was not present and may provide a clinically and laboratory relevant, relatively inexpensive, high resolution imaging method for imaging in the presence of bone. This allows tumor, muscle, tendon, ligament or cartilage disease monitoring for therapy and general laboratory or clinical settings. The method has proven useful in breast imaging and is generalized here to high-resolution quantitative imaging in the presence of bone. The laboratory data are acquired in ~ 12 min and the reconstruction in ~ 24 min—approximately 200 times faster than previously reported simulations in the literature. Such fast reconstructions with real data require careful calibration, adequate data redundancy from a 2D array of 2048 elements and a paraxial approximation. The imaging results show that tissue surrounding the high impedance region is artifact free and has correct speed of sound at sub-mm resolution.

Speed of sound ultrasound transmission tomography image reconstruction based on Bézier curves

Speed of Sound (SoS) maps from ultrasound tomography (UST) provide valuable quantitative information for soft tissue characterization and identification of lesions, making this technique interesting for breast cancer detection. However, due to the complexity of the processes that characterize the interaction of ultrasonic waves with matter, classic and fast tomographic algorithms such as back-projection are not suitable. Consequently, the image reconstruction process in UST is generally slow compared to other more conventional medical tomography modalities. With the aim of facilitating the translation of this technique into real clinical practice, several reconstruction algorithms are being proposed to make image reconstruction in UST to be a fast and accurate process. The geometrical acoustic approximation is often used to reconstruct SoS with less computational burden in comparison with full-wave inversion methods. In this work, we propose a simple formulation to perform on-the-flight reconstruction for UST using geometrical acoustics with refraction correction based on quadratic Bézier polynomials. Here we demonstrate that the trajectories created with these polynomials are an accurate approximation to reproduce the refracted acoustic paths connecting the emitter and receiver transducers. The method is faster than typical acquisition times in UST. Thus, it can be considered a step towards real-time reconstructions, which may contribute to its future clinical translation.

Dual Modality EIT-UTT for Water Dominate Three-Phase Material Imaging

Three-phase material imaging such as oil, gas and water is a critical problem in many processes. Monitoring and separation of each phase before corresponding process can be a key to realise cost efficiency production. In the oil and gas industry such a tool can generate great environmental benefits. In recent years, several multi-modality imaging systems are being adapted for such an application. It is not possible to gain information on three phase flow using a single imaging modality that can be deployed in production field. For a three-phase flow dominated by water phase, this is more challenging. The capability of the majority of current dual-modality systems was only demonstrated under limited flow regime conditions. This paper presents a novel combined imaging system including electrical impedance tomography (EIT), and ultrasound transmission tomography (UTT) for mapping three-phase flow. In water dominate mode, the EIT is able to image the nonconductive phases of oil and gas in a water dominate background phase, but not able to separate oil and gas. The EIT two-phase imaging then complimented with the speed of sound imaging of the UTT, which can separate liquid (oil and water) and gas. A dual modality EIT-UTT system combining a 32-electrode EIT array and a 32-transducer UTT sensor array is developed to demonstrate this novel three-phase material imaging. The concept was demonstrated using simulation study and then shown with experimental lab tests. Measurement principles and method are described, experiment based on several three-phase flow scenarios are established, and the results show successful distinguishably for all three phases.

Logistic Regression for Machine Learning in Process Tomography

The main goal of the research presented in this paper was to develop a refined machine learning algorithm for industrial tomography applications. The article presents algorithms based on logistic regression in relation to image reconstruction using electrical impedance tomography (EIT) and ultrasound transmission tomography (UST). The test object was a tank filled with water in which reconstructed objects were placed. For both EIT and UST, a novel approach was used in which each pixel of the output image was reconstructed by a separately trained prediction system. Therefore, it was necessary to use many predictive systems whose number corresponds to the number of pixels of the output image. Thanks to this approach the under-completed problem was changed to an over-completed one. To reduce the number of predictors in logistic regression by removing irrelevant and mutually correlated entries, the elastic net method was used. The developed algorithm that reconstructs images pixel-by-pixel is insensitive to the shape, number and position of the reconstructed objects. In order to assess the quality of mappings obtained thanks to the new algorithm, appropriate metrics were used: compatibility ratio (CR) and relative error (RE). The obtained results enabled the assessment of the usefulness of logistic regression in the reconstruction of EIT and UST images.

Optimization Approach for Image Forming in Ultrasound Transmission Tomography (UTT): Real Data Case

Effective image reconstruction algorithm that could be used in Ultrasound Transmission Tomography (UTT) is presented in this paper. The reconstruction process was bringing over to the solution of the inverse problem which was converted to the optimization task. The optimization parameters were selected as follows: a position vector defining the position of the obstacle centre (the length of the position vector and its angle) and the internal radius of the test objects (obstacles). In this case, sixteen trial objects were selected, which gives 48th optimization parameters (three parameters for each trial object). During the optimization process some of them could diminish to zero; the others would change the position and dimensions in such a way that the calculated signal become as close as possible to the measured one. The objective function and linear inequality constrain were defined. The optimization process is very sensitive how far away from the optimal solution the starting point was defined. That is why three cases of the selection of the starting point to the optimization process were considered.

Quantitative assessment of breast density using transmission ultrasound tomography.

PurposeBreast density is important in the evaluation of breast cancer risk. At present, breast density is evaluated using two‐dimensional projections from mammography with or without tomosynthesis using either (a) subjective assessment or (b) a computer‐aided approach. The purpose of this work is twofold: (a) to establish an algorithm for quantitative assessment of breast density using quantitative three‐dimensional transmission ultrasound imaging; and (b) to determine how these quantitative assessments compare with both subjective and objective mammographic assessments of breast density.MethodsWe described and verified a threshold‐based segmentation algorithm to give a quantitative breast density (QBD) on ultrasound tomography images of phantoms of known geometric forms. We also used the algorithm and transmission ultrasound tomography to quantitatively determine breast density by separating fibroglandular tissue from fat and skin, based on imaged, quantitative tissue characteristics, and compared the quantitative tomography segmentation results with subjective and objective mammographic assessments.ResultsQuantitative breast density (QBD) measured in phantoms demonstrates high quantitative accuracy with respect to geometric volumes with average difference of less than 0.1% of the total phantom volumes. There is a strong correlation between QBD and both subjective mammographic assessments of Breast Imaging ‐ Reporting and Data System (BI‐RADS) breast composition categories and Volpara density scores — the Spearman correlation coefficients for the two comparisons were calculated to be 0.90 (95% CI: 0.71–0.96) and 0.96 (95% CI: 0.92–0.98), respectively.ConclusionsThe calculation of breast density using ultrasound tomography and the described segmentation algorithm is quantitatively accurate in phantoms and highly correlated with both subjective and Food and Drug Administration (FDA)‐cleared objective assessments of breast density.

Transmission\u2013reflection optoacoustic ultrasound (TROPUS) computed tomography of small animals

Rapid progress in the development of multispectral optoacoustic tomography techniques has enabled unprecedented insights into biological dynamics and molecular processes in vivo and noninvasively at penetration and spatiotemporal scales not covered by modern optical microscopy methods. Ultrasound imaging provides highly complementary information on elastic and functional tissue properties and further aids in enhancing optoacoustic image quality. We devised the first hybrid transmission–reflection optoacoustic ultrasound (TROPUS) small animal imaging platform that combines optoacoustic tomography with both reflection- and transmission-mode ultrasound computed tomography. The system features full-view cross-sectional tomographic imaging geometry for concomitant noninvasive mapping of the absorbed optical energy, acoustic reflectivity, speed of sound, and acoustic attenuation in whole live mice with submillimeter resolution and unrivaled image quality. Graphics-processing unit (GPU)-based algorithms employing spatial compounding and bent-ray-tracing iterative reconstruction were further developed to attain real-time rendering of ultrasound tomography images in the full-ring acquisition geometry. In vivo mouse imaging experiments revealed fine details on the organ parenchyma, vascularization, tissue reflectivity, density, and stiffness. We further used the speed of sound maps retrieved by the transmission ultrasound tomography to improve optoacoustic reconstructions via two-compartment modeling. The newly developed synergistic multimodal combination offers unmatched capabilities for imaging multiple tissue properties and biomarkers with high resolution, penetration, and contrast.

Quantitative transmission ultrasound tomography: Imaging and performance characteristics.

PurposeQuantitative Transmission (QT) ultrasound has shown promise as a breast imaging modality. This study characterizes the performance of the latest generation of QT ultrasound scanners: QT Scanner 2000.MethodsThe scanner consists of a 2048‐element ultrasound receiver array for transmission imaging and three transceivers for reflection imaging. Custom fabricated phantoms were used to quantify the imaging performance parameters. The specific performance parameters that have been characterized are spatial resolution (as point spread function), linear measurement accuracy, contrast to noise ratio, and image uniformity, in both transmission and reflection imaging modalities.ResultsThe intrinsic in‐plane resolution was measured to be better than 1.5 mm and 1.0 mm for transmission and reflection modalities respectively. The linear measurement accuracy was measured to be, on average, approximately 1% for both the modalities. Speed of sound image uniformity and measurement accuracy were calculated to be 99.5% and <0.2% respectively. Contrast to noise ratio (CNR) measurements vary as a function of object size.ConclusionsThe results show an improvement in the imaging performance of the system in comparison to earlier ultrasound tomography systems, which are applicable to clinical applications of the system, such as breast imaging.