Phase coherence imaging of grained materials

A Very Large Cardiac Channel Data Database (VLCD) Used to Evaluate Global Image Coherence (GIC) as an In Vivo Image Quality Metric

Ultrasound image quality is of utmost importance for a clinician to reach a correct diagnosis. Conventionally, image quality is evaluated using metrics to determine the contrast and resolution. These metrics require localization of specific regions and targets in the image such as a region of interest (ROI), a background region, and/or a point scatterer. Such objects can all be difficult to identify in in-vivo images, especially for automatic evaluation of image quality in large amounts of data. Using a matrix array probe, we have recorded a Very Large cardiac Channel data Database (VLCD) to evaluate coherence as an in vivo image quality metric. The VLCD consists of 33280 individual image frames from 538 recordings of 106 patients. We also introduce a global image coherence (GIC), an in vivo image quality metric that does not require any identified ROI since it is defined as an average coherence value calculated from all the data pixels used to form the image, below a preselected range. The GIC is shown to be a quantitative metric for in vivo image quality when applied to the VLCD. We demonstrate, on a subset of the dataset, that the GIC correlates well with the conventional metrics contrast ratio (CR) and the generalized contrast-to-noise ratio (gCNR) with R = 0.74 ( ) and R = 0.62 ( ), respectively. There exist multiple methods to estimate the coherence of the received signal across the ultrasound array. We further show that all coherence measures investigated in this study are highly correlated ( 0.9 and ) when applied to the VLCD. Thus, even though there are differences in the implementation of coherence measures, all quantify the similarity of the signal across the array and can be averaged into a GIC to evaluate image quality automatically and quantitatively.

Real-time ultrasound phase imaging

The Correlation-Based (CB) imaging method is characterized by its high spatial resolution capabilities, but it is known to require heavy computational resources due to its high complexity. This paper shows that the CB imaging method can be used to estimate the phase of the complex reflection coefficients contained in the observation window. The resulting Correlation-Based Phase Imaging (CBPI) method can be used to segment and identify different features or tissue elasticity variations in a given medium. A Numerical validation is first proposed by considering a set of fifteen point-like scatterers on a Verasonics Simulator. Then, three experimental datasets are used to show the potential of CBPI on scatterers and specular reflectors. In vitro imaging results are first presented to show that CBPI allows retrieving phase information on hyperechoic reflectors, but also on weak reflectors such as elasticity targets. It is demonstrated that CBPI helps distinguishing regions of different elasticity, but of same low-contrast echogenicity, which is otherwise impossible with standard B-mode or Synthetic Aperture Focusing Techniques (SAFT). Then, CBPI of a needle in an ex vivo chicken breast is performed to show that the method works on specular reflectors. It is shown that the phase of the different interfaces associated to the first wall of the needle are well reconstructed using CBPI. The heterogeneous architecture used to enable real-time CBPI is presented. A Nvidia GeForce RTX 2080 Ti Graphics Processing Unit (GPU) is used to process the real-time acquired signals from a Verasonics Vantage 128 research echograph. Frame rates of 18 frames per second are achieved for the whole acquisition and signal processing chain on standard a 500 × 200 pixels grid.

Transcranial 3D ultrasound localization microscopy using a large element matrix array with a multi-lens diffracting layer: anin vitrostudy

Objective. Early diagnosis and acute knowledge of cerebral disease require to map the microflows of the whole brain. Recently, ultrasound localization microscopy (ULM) was applied to map and quantify blood microflows in 2D in the brain of adult patients down to the micron scale. Whole brain 3D clinical ULM remains challenging due to the transcranial energy loss which reduces significantly the imaging sensitivity.Approach. Large aperture probes with a large surface can increase both the field of view and sensitivity. However, a large active surface implies thousands of acoustic elements, which limits clinical translation. In a previous simulation study, we developed a new probe concept combining a limited number of elements and a large aperture. It is based on large elements, to increase sensitivity, and a multi-lens diffracting layer to improve the focusing quality. In this study, a 16 elements prototype, driven at 1 MHz frequency, was made andin vitroexperiments were performed to validate the imaging capabilities of this new probe concept.Main results. First, pressure fields emitted from a large single transducer element without and with diverging lens were compared. Low directivity was measured for the large element with the diverging lens while maintaining high transmit pressure. The focusing quality of 4 × 3cm matrix arrays of 16 elements without/with lenses were compared.In vitroexperiments in a water tank and through a human skull were achieved to localize and track microbubbles in tubes.Significance.ULM was achieved demonstrating the strong potential of multi-lens diffracting layer to enable microcirculation assessment over a large field of view through the bones.

Secondary Interface Echoes Suppression for Immersion Ultrasonic Imaging Based on Phase Circular Statistics Vector

Immersion ultrasonic phased array imaging technology offers great advantages, particularly in coupling and automatic detection of industrial non-destructive testing (NDT). To suppress the influence of secondary interface echoes in the immersion ultrasonic phased array imaging, a novel phase circular statistics vector (PCSV) weighting method is proposed in this paper. Firstly, the PCSV factor matrix is established according to the phase consistency of the echo signals. Secondly, due to the higher phase coherence of the defect echo, the PCSV factor matrix is used to weight the TFM image to suppress the secondary interface echo. The result shows the secondary interface echoes are effectively suppressed in the total focusing method (TFM) image on a 0~40 dB scale. It is also shown that PCSV weighting could not only suppress the secondary interface echoes but also improved the image quality in terms of SNR and lateral resolution by comparing with traditional TFM.

Improving photoacoustic imaging in low signal-to-noise ratio by using spatial and polarity coherence

To suppress the noise and sidelobe of photoacoustic images, a method is proposed combined with spatial coherence and polarity coherence. In this method, PA signals are delayed, multiplied, then performed polarity coherence, and finally summed. The polarity of delayed-and-multiplied signals rather than the amplitude is considered in polarity coherence operation. The polarity coherence factor is calculated based on the standard deviation of the polarity. Then, the factor as weights is applied to the coherent sum output after spatial autocorrelation to finally obtain the image. The simulated and experimental results prove that the noise level can be effectively suppressed due to its relatively low polarity coherence factor. Compared with the delay-and-sum method, the quantitative results in simulations show that the image contrast and full-width at half-maximum of the proposed method increase by about 227.0 % and 56.5 % when the signal-to-noise ratio of the raw signal is 0 dB, respectively. Besides achieving a better image contrast, this method obtains improvements in sidelobe attenuation and has a narrow main lobe.

Correlation-based ultrasound imaging of strong reflectors with phase coherence filtering

Two main metrics are usually employed to assess the quality of medical ultrasound (US) images, namely the contrast and the spatial resolution. A number of imaging algorithms have been proposed to improve one of those metrics, often at the expense of the other one. This paper presents the application of a correlation-based ultrasound imaging method, called Excitelet, to medical US imaging applications and the inclusion of a new Phase Coherence (PC) metric within its formalism. The main idea behind this algorithm, originally developed and validated for Non-Destructive Testing (NDT) applications, is to correlate a reference signal database with the measured signals acquired from a transducer array. In this paper, it is shown that improved lateral resolutions and a reduction of imaging artifacts are obtained over the Synthetic Aperture Focusing Technique (SAFT) when using Excitelet in conjunction with a PC filter. This novel method shows potential for the imaging of specular reflectors, such as invasive surgical tools. Numerical and experimental results presented in this paper demonstrate the benefit, in terms of contrast and resolution, of using the Excitelet method combined with PC for the imaging of strong reflectors.

Time domain imaging of extended transient noise sources using phase coherence

An acoustic imaging algorithm is proposed herein for transient noise source time reconstruction. Time domain formulations are not well suited for acoustic imaging because of the size of the resulting system to be inversed. Based on the phase coherence principle widely used in ultrasound imaging and image processing, the first step of the algorithm consists in proposing the phase coherence metric used to reject pixels that are unlikely to contribute to the radiated sound field. This translates in a reduction of the domain size and ill-posedness of the problem. In the second step, the inverse problem is solved using the Tikhonov regularization and the generalized cross-validation to extract the vibration field on the imaging domain. Two test cases are considered: a simulated baffled piston and a panel submitted to a mechanical impact in anechoic conditions. The actual vibration field of the panel is measured with an optical technique for reference. In both numerical and experimental cases, the reconstructed vibration field using the proposed approach compares well with their respective reference. The results confirm that transient excitations can be localized and quantified with the proposed approach, in contrast with the classical time-domain beamforming that dramatically overestimates its magnitude.

A Portable Ultrasound Imaging System Utilizing Deep Generative Learning-Based Compressive Sensing On Pre-Beamformed RF Signals

Recent advances in the unsupervised and generative models of deep learning have shown promise for application in biomedical signal processing. In this work, we present a portable resource-constrained ultrasound (US) system trained using Variational Autoencoder (VAE) network which performs compressive-sensing on pre-beamformed RF signals. The encoder network compresses the RF data, which is further transmitted to the cloud. At the cloud, the decoder reconstructs back the ultrasound image, which can be used for inferencing. The compression is done with an undersampling ratio of 1/2, 1/3, 1/5 and 1/10 without significant loss of the resolution. We also compared the model by state-of-the-art compressive-sensing reconstruction algorithm and it shows significant improvement in terms of PSNR and MSE. The innovation in this approach resides in training with binary weights at the encoder, shows its feasibility for the hardware implementation at the edge. In the future, we plan to include our field-programmable gate array (FPGA) based design directly interfaced with sensors for real-time analysis of Ultrasound images during medical procedures.

A methodology for evaluating detection performance of ultrasonic array imaging algorithms for coarse-grained materials

Improving the ultrasound inspection capability for coarse-grained metals remains of longstanding interest and is expected to become increasingly important for next-generation electricity power plants. Conventional ultrasonic A-, B-, and C-scans have been found to suffer from strong background noise caused by grain scattering, which can severely limit the detection of defects. However, in recent years, array probes and full matrix capture (FMC) imaging algorithms have unlocked exciting possibilities for improvements. To improve and compare these algorithms, we must rely on robust methodologies to quantify their performance. This article proposes such a methodology to evaluate the detection performance of imaging algorithms. For illustration, the methodology is applied to some example data using three FMC imaging algorithms; total focusing method (TFM), phase-coherent imaging (PCI), and decomposition of the time-reversal operator with multiple scattering filter (DORT MSF). However, it is important to note that this is solely to illustrate the methodology; this article does not attempt the broader investigation of different cases that would be needed to compare the performance of these algorithms in general. The methodology considers the statistics of detection, presenting the detection performance as probability of detection (POD) and probability of false alarm (PFA). A test sample of coarse-grained nickel super alloy, manufactured to represent materials used for future power plant components and containing some simple artificial defects, is used to illustrate the method on the candidate algorithms. The data are captured in pulse-echo mode using 64-element array probes at center frequencies of 1 and 5 MHz. In this particular case, it turns out that all three algorithms are shown to perform very similarly when comparing their flaw detection capabilities.

Instantaneous phase threshold for reflector detection in ultrasonic images

A method for reflector detection, based on the instantaneous phase of the aperture data for ultrasonic images, is proposed. The instantaneous phase (IP) image is obtained by replacing the amplitude information by the instantaneous phase in the delay-and-sum (DAS) beamforming. From the analysis of the IP image, a threshold level is defined in terms of the number of signals used for imaging. This threshold is applied to the IP image, resulting in a two-level image which gives a statistical indication of whether the pixels of a region in the image are related to a reflector or noise/artifacts. Because the proposed method uses only the instantaneous phase of the signals, it is less sensitive to attenuation than conventional DAS amplitude images. The point spread function of a 32-element array with half-wavelength pitch at 5 MHz in water is simulated and the reflector is detected for signal-to-noise ratio values larger than -29.6 dB. A phantom and an aluminum plate with artificial defects are tested with the proposed technique, using linear arrays of 64 and 16 elements, respectively. When compared with DAS amplitude images and with two-level images obtained by thresholding the amplitude images using empirical threshold values, the proposed technique reduced artifacts and dead zone, and detected all reflectors, increasing reflectors' detectability and decreasing the occurrence of false indication of reflectors. The proposed technique can be used as additional information for amplitude image analysis, with the advantages that it does not need time-gain compensation and that it considers an objective threshold value.

Comparison of ultrasonic array imaging algorithms for nondestructive evaluation

Ultrasonic array imaging algorithms have been widely used and developed in nondestructive evaluation in the last 10 years. In this paper, three imaging algorithms [total focusing method (TFM), phase-coherent imaging (PCI), and spatial compounding imaging (SCI)] are compared through both simulation and experimental measurements. In the simulation, array data sets were generated using a hybrid forward model containing a single defect among a multitude of randomly distributed point scatterers to represent backscatter from material microstructure. The number of point scatterers per unit area and their scattering amplitude were optimized to reduce computation cost. The SNR of the final images and their resolution were used to indicate the quality of the different imaging algorithms. The images of different types of defects (point reflectors and planar cracks) were used to investigate the robustness of the imaging algorithms. It is shown that PCI can yield higher image resolution and higher SNR for defects in material with weak backscatter than TFM, but that the images of cracks are distorted. Overall, TFM is the most robust algorithm across a range of different types of defects. It is also shown that the detection limit of all three imaging algorithms is almost equal for weakly scattering defects.