Modified Distorted Born Iterative Method for Ultrasound Tomography by Random Sampling

The greatest advantage of scattering theory-based ultrasound tomography (UT) is its ability to investigate small structures. DBIM is the Distorted Born Iterative Method. The nearest neighbour interpolation method is used to enhance the reconstruction performance and reduce the reconstruction time. The raw (N 1 × N 1) and dense (N 2 × N 2) meshed integration areas are reconstructed in NN 1 and NN 2 iterations, respectively. However, choosing the best value of NN 1 to get the highest performance was not mentioned in previous works. If it is not well chosen, the reconstruction quality is even worse than that when using no interpolation. This study proposes a method to enhance the UT reconstruction by using the nearest neighbour interpolation (MR-DBIM). The corresponding algorithms are specified by the graphical concurrent programming language of Sleptsov nets. Some significant results are (1) the MR-DBIM is only meaningful when (i.e. sparse scattering domain); (2) the best performance is obtained in the DBIM when Nt = Nr , but in the MR-DBIM when Nr = 2Nt ; (3) the well-investigated value of NN 1 is 2 when and is 3 when .

With its consideration for nonlinear scattering phenomena, the distorted Born iterative method (DBIM) is known to provide images superior to those of linear tomographic methods. However, the complexity involved with the production of superior images has prevented DBIM from overtaking simpler imaging schemes in commercial applications. The iterative process and need to solve the forward-scattering problem multiple times make DBIM a slow algorithm compared to diffraction tomography. Fortunately, as computer prices continue to decline, it is becoming easier to assemble large, distributed computer clusters from low-cost personal computer systems. These are well-suited to DBIM inversions, and offer great promise in accelerating the method. Traditional frequency-domain DBIM formulations produce an image by inverting the Fréchet derivative. If the derivative is treated as a matrix, it is costly to construct and awkward to invert on distributed computer systems. This paper presents an interpretation of the Fréchet derivative that is ideal for parallel-computing applications. As a bonus, this formulation reduces the storage requirements of DBIM implementations, making it possible to invert larger problems on a fixed system.

Distorted Born iterative method (DBIM) using multi-frequency information has been studied and applied in ultrasound tomography. However, the use of different frequencies in different iterations in the DBIM method is not used consistently. The value of the frequency hopping step is often chosen depending on the simulation builder or experimenter. Based on the multi-frequency combination technique, this paper suggests an effective multi-frequency combination procedure to improve the quality of reconstructing ultrasound images using fundamental tone and overtones (FTaOT). The numerical simulation results show that the normalized error of the suggested scheme is decreased by 45% in comparison with the dual-frequency method. Other multi-frequency combination scenarios are also simulated to demonstrate the feasibility of the proposed method.

Microwave non-destructive testing (NDT) is promising for detection of an air cavity or a metallic corrosion buried into concrete road or tunnel. The distorted born iterative method (DBIM) is one of the most effective approaches to reconstruct dielectric map and recognize a high contrast object. However, in an actual NDT observation model, it must be assumed that only reflection field is available, which makes the ill-posed problem extremely difficult. To solve this problem, the range points migration (RPM) based object area extraction scheme is incorporated into the DBIM, where the area of region of interest (ROI) is considerably downsized to reduce the number of unknowns in the DBIM. The finite-difference time-domain (FDTD) based numerical simulation tests demonstrate that our proposed method effectively enhance the accuracy of dielectric map reconstruction for the sparsely distributed object model.

A new microwave image reconstruction method is proposed to recover a nonsparse object using the iterative method with adaptive thresholding for compressed sensing (IMATCS) method. First, a dual-mesh method discretizes the object using the Distmesh generator tool, which automatically generates size functions and adapts to the curvature and the feature size of the geometry. Near field scattered data collected from a circular phantom are used to solve the inverse scattering problem using the distorted Born iterative method (DBIM). At every iteration during DBIM, the forward problem is formulated as an underdetermined set of linear equations. Then, the IMATCS method is applied to solve the linear equations. IMATCS is a $L_{2}$ -regularized approach to solve the sparse recovery problem, which improves the robustness of the algorithm. Next, the nondecimated wavelet transform (NDWT) method is applied to transform the nonsparse signal into a sparse signal which acts as an input to the IMATCS process. As a result, the new proposed NDWT based on IMATCS method (NDW-IMATCS) is able to recover the nonsparse signal and leads to the reconstruction results. Finally, we demonstrate that our dual-mesh method combined with the NDW-IMATCS algorithm leads to fast, accurate, and stable reconstructions of nonsparse objects.

For an ultrasound blurry image with more dark pixels and the blurry ultrasound image is not sparse enough after the bright channel prior deblurring. In order to make more effective use of the image information and enhance the sparsity of the ultrasound images obtained after deblurring, a method of blind ultrasound image deblurring based on quadratic sparse bright channel prior. Firstly, a quadratic sparse bright channel is proposed based on the bright channel. Secondly, the prior information of the image is obtained by using the quadratic sparse bright channel. Then, the clear image and blur kernel are estimated by half-quadratic splitting. Finally, the deblurring experiments are carried out on the ultrasound image set, and compared with other deblurring algorithms. Experimental results show that this algorithm has higher feasibility and superiority.

Segmenting the lesion region from 2D ultrasound (US) images is an importance step in defining the intra-operative planning of computer-assisted therapy. However, it still remains a challenge owing to two reasons: (1) The signal-to-noise ratio (SNR) of the US images is originally low, and the inhomogeneous distribution of intensity causes local fuzzy boundaries. (2) The deformation of soft tissue causes makes the geometry contour of the segmentation area complex. Because of these factors, the classical segmentation methods do not yield the desired results in US images. To solve these problems, a novel segmentation method based on a dynamics statistical shape model is proposed. In this study, first, a radial time series model was defined for use as a parametric shape model of the lesion region, and a stochastic difference equation (SDE) was used as the contour dynamics generating model; then, the coefficients of the dynamics generating model and the shape prior probability were deduced by utilizing the property of Fokker-Planck equation (FPE) and training the samples. This statistical shape model (SSM) was referred to as the SF-SSM. Furthermore, a radial profile feature model (RPFM) was developed based on the statistical features of the intensity distribution from the inside to outside of the lesion region and based on the radial time series model. The RPFM provided a likelihood probability for the prior shape. Finally, through the segmentation optimization process, the maximum posteriori process was determined. In order to verify the performance of our method, we used real clinical ultrasound images as the training and test sets. We compared the proposed model with three well-known segmentation methods for the same test set. The experimental results showed that the proposed method provided more accurate results than the other methods for different quality US images. Furthermore, the friendly initialization of the proposed method improves the efficiency of interactive segmentation, thus benefitting computer-assisted therapy.

With the advantages of non-radiation and low-cost, ultrasound imaging has been widely used in clinical diagnosis. However, due to the compromise between temporal and spatial resolution, the traditional ultrasound imaging method which collects images line by line fails to obtain the images at a high frame rate. Ultrafast ultrasound imaging method based on the plane-wave emission can achieve a high frame rate with the capability for instantaneous hemodynamic imaging of neurovascular response. Besides, by the coherent compounding of the echo signals received from emitting a set of tilting plane-waves, the image quality can be improved in terms of resolution, contrast and signal-to-noise ratio (SNR). Considering the fact that received signals are the mixture of echo signals from the low-speed soft tissue and high-speed blood flow, a clutter filtering method is used to remove the signals of soft tissue. In this study, the ultrafast ultrasound sequence of emission and reception is designed to image the spinal cord by using the groups of multiple steering-angle plane-waves. The so-called f-k migration algorithm based on an exploding reflector model (ERM) is used for coherent plane-wave compounding. Eigenvalue decomposition (EVD) is then applied to tissue and blood signal extraction. The static tissue signals correspond to eigenvectors with low Doppler frequency shift and large magnitude eigenvalue while the high-speed blood flow signals correspond to eigenvectors with high Doppler frequency shift and small eigenvalue. Therefore, frequency and amplitude thresholds can be applied to the accurate separation of the blood component and the tissue component. After the signal extraction, the hemodynamic imaging of blood vessels can thus be obtained from the power Doppler results. The experiments are carried out by using a programmable ultrasonic array system and a high-frequency linear array transducer L22-14vX with a central frequency of 15.625 MHz. The sample acquisition frequency is set to be 62.5 MHz. In rat experiments <i>in vivo</i>, 14040 angle-stilting images per second are compounded into 520 images, each of which is compounded from 27 tilting images (the tilting angles ranging from –10° to 10°). The experiments are conducted on the anesthetized rats with part of the vertebral plate removed. The ultrafast B-mode images are acquired from a 14.0 mm ×12.7 mm region-of-interest. The 520 frames acquired in one second are processed by the clutter filter based on eigenvalue decomposition and Doppler shift analysis. The eigenvectors and eigenvalues corresponding to the soft tissue are discarded. The power Doppler images of the spinal cord micro-vessels are obtained. The experimental results indicate that the ultrafast ultrasound Doppler imaging method is effective for monitoring the hemodynamic variation in spinal cord. The micro-hemorrhage can be identified from the power Doppler images. The quantitative results indicate that the SNR increases with the steering angles increasing. Compared with the results obtained by using 9 steering angles, 5 dB SNR enhancement can be obtained by using the 27 steering angles. In conclusion, the ultrafast ultrasound Doppler technology has the potential applications in spinal cord microvascular imaging and hemodynamic evaluation of neurovascular function of spinal cord.

Aim: To evaluate very-high-frequency (VHF) ultrasound imaging as a new method to detect and quantify early corneal epithelium changes induced by chronic exposure to a benzalkonium-chloride-containing antiglaucoma drug. Methods: Timolol preserved with 0.01% benzalkonium chloride solution was applied b.i.d. in 1 eye of 10 rabbits for 56 days. Unpreserved timolol solution was used as control. Ocular surface changes were assessed weekly combining clinical examinations, in vivo 60-MHz ultrasound imaging and ex vivo histological analysis. Results: VHF ultrasound imaging allowed quantitative measurement of corneal epithelium thickness and qualitative imaging of toxic epithelial damage. It revealed significantly decreased epithelial thickness in vivo as early as the 21st day of treatment (40.75 ± 1.72 µm at D0 vs. 39 ± 2 at D21, vs. 31.9 ± 2.98 at D56; p = 0.017 and p = 0.005, respectively). The first clinical changes appeared from the 42nd day of treatment (conjunctival redness, conjunctival staining and corneal staining; D56 compared to D0: p = 0.005, 0.01 and 0.004, respectively) and then correlated with VHF ultrasound data. Epithelial thickness measured with VHF ultrasound was correlated with histological epithelial pachymetry (p < 0.001) and with the corneal damage score assessed with scanning electron microscopy (p = 0.038). Conclusion: VHF ultrasound imaging provided an early in vivo diagnosis of corneal epithelium pathology induced by chronic exposure to a preserved glaucoma drug, before the first clinical evidence of ocular toxicity. It could be a new reproducible method to detect the toxicity of glaucoma medication so that therapy can then be adapted.

The sensitivity of phase-sensitive detectors, such as piezoelectric detectors, becomes increasingly directional as the detector element size increases. In contrast, pyroelectric sensors, which are phase-insensitive, retain their omni-directionality even for large element sizes, although they have significantly poorer temporal resolution. This study uses numerical models to examine whether phase-insensitive detectors can be used advantageously in ultrasound tomography, specifically absorption tomography, when the number of detectors is sparse. We present measurement models for phase-sensitive and phase-insensitive sensors and compare the quality of the absorption reconstructions between these sensor types based on relative error and image contrast metrics. We perform the inversion using synthetic data with a Jacobian-based linearized matrix inversion approach.

This paper presents an efficient three-dimensional nonlinear electromagnetic inversion method in a multilayered medium for geophysical exploration. The stabilized biconjugate-gradient fast Fourier transform algorithm is used for forward modeling, whereas the distorted Born iterative method is used in the inversion. The conjugate-gradient method is applied at each inversion iteration to minimize the cost function. The usage of an iterative solver based on the FFT algorithm and the developed recursive matrix method combined with an interpolation technique to evaluate the layered medium Green's functions rapidly, make this method highly efficient, with the requirement of very low time and memory, O (N log N ) and O (N) respectively. Numerical experiments about the 3D forward modeling with application in Borehole to Surface Electromagnetic Method will be presented in this paper; in addition, we will show the examples about 3D inversion applied in geophysical exploration. All these results will demonstrate the high efficiency and accuracy of the proposed method.

This paper presents a microwave tomography system for ischemic stroke. The developed device consists of a measurement prototype, a matrix switch and a vector network analyzer(VNA). and it equipped with an efficient imaging method for the reconstruction of the distribution of the relative permittivity of the human body under test. It has been preliminarily verified by experimental data. The results show that the system can effectively detect inclusions with different sizes and positions in the head model under consideration.

Wearable ultrasound bioelectronics for healthcare monitoring

This paper presents a wavelet-based hybrid threshold method according to the soft- and hard-threshold functions proposed by Donoho. The wavelet-based hybrid threshold method may help doctors to know more details on the liver disease through denoising the ultrasound image of the liver. First of all, an analytical expression for the hybrid threshold function is discussed. The wavelet-based hybrid threshold method is then investigated for ultrasound image of the liver. Finally, we test the influence of this parameter on the proposed method with the real ultrasound image corrupted by speckle noise with different variances. Moreover, we compare the proposed method under the varying parameters with the soft-threshold function and the hard-threshold function. Three metrics, which are correlation coefficient, edge preservation index and structural similarity index, are measured to quantify the denoised results of ultrasound liver image. Experimental results demonstrate the potential of the proposed method for ultrasound liver image denosing.

Chirp coded excitation is an effective method to improve the signal-to-noise ratio (SNR) and penetration depth of high-frequency endoscopic ultrasound (EUS) imaging. In coded excitation, pulse compression is applied to compress the elongated coded signals into a short pulse, which determines the final imaging performance, including spatial resolution and SNR. However, with the current pulse compression methods, it is hard to get high performance in the peak sidelobe level (PSL), image contrast, and axial resolution at the same time. To solve this problem, in this article, a new method named compressed pulse weighting method (CPWM) was proposed based on the combination of two kinds of pulse compression signals. A brief theoretical derivation proved the feasibility of method. The proposed method was evaluated by the simulation and phantom experiments. Compared with traditional method, the results showed that the proposed adaptive weighting method can provide increases of 32.42% in the penetration depth, 9.48 dB in the SNR, 5.60 dB in the contrast ratio (CR), 5.46 in the contrast-to-noise ratio (CNR), and 0.13 mm in the axial imaging resolution for 12-MHz EUS. Therefore, this method can effectively improve the ultrasound penetration depth and imaging quality, which made it have good potential for high-frequency ultrasound imaging.