Sigma-delta receive beamformer based on cascaded reconstruction for ultrasound imaging application

A pre-delay reconstruction sigma-delta beamformer (SDBF) was recently proposed to achieve a higher level of integration in ultrasound imaging systems. Nevertheless, the high-order reconstruction filter used in each channel of SDBF makes the beamformer highly complex. The beamformer can be simplified by reconstructing the signal after the delay-andsum process with only one filter. However, this post-delay reconstruction-based design degrades image quality when dynamic focusing is performed. This paper shows that employing a simple pre-delay filter is sufficient to achieve similar performance as conventional pre-delay reconstruction SDBF, as long as the pre-delay filter provides the required pre-delay signalto- quantization noise ratio (SQNR). Based on this finding, we proposed a cascaded reconstruction beamformer that uses a boxcar filter as the pre-delay filter in each channel. Simulations using real phantom data demonstrate that the proposed beamforming method can achieve a contrast resolution comparable to that of the pre-delay reconstruction beamforming method. In addition, the hardware can be greatly simplified compared with the pre-delay reconstruction beamformers.     

采用反向投影算法进行宽带合成孔径声纳数据处理与图像重建

文中提出了宽带合成孔径声纳(synthetic aperture Sonar，简称SAS)成像的反向投影算法(back pmjection，简称BP)。该算法是在时间-空间域中对合成孔径线列阵中备个阵元接收回波的所有频率分量进行相干求和，以充分利用合成孔径上所有回波的能量，从而得到理想的SAS图像。同时，文章中分析了BP算法实现过程中拖尾(tall)现象的产生机理，对BP重建图像进行了斜坡滤波处理。并对载频为15kHz,带宽为20kHz的SAS系统进行了仿真，结果验证了这种算法的有效性。     

Small-kernel superresolution methods for microscanning imaging systems

Two computationally efficient methods for superresolution reconstruction and restoration of microscanning imaging systems are presented. Microscanning creates multiple low-resolution images with slightly different sample-scene phase shifts. The digital processing methods developed here combine the low-resolution images to produce an image with higher pixel resolution (i.e., superresolution) and higher fidelity. The methods implement reconstruction to increase resolution and restoration to improve fidelity in one-pass convolution with a small kernel. One method uses a small-kernel Wiener filter and the other method uses a parametric cubic convolution filter. Both methods are based on an end-to-end, continuous-discrete-continuous microscanning imaging system model. Because the filters are constrained to small spatial kernels they can be efficiently applied by convolution and are amenable to adaptive processing and to parallel processing. Experimental results with simulated imaging and with real microscanned images indicate that the small-kernel methods efficiently and effectively increase resolution and fidelity.     

CCD高分辨成像的梯度解析法

基于序列图像重建的高分辨成像技术需要获取互有位移的序列图像,并需利用图像重建算法进行高分辨率图像重建。为此,设计了一种利用压电陶瓷体控制CCD位移来获取互有微小位移的序列图像的装置,在此基础上提出了一种基于梯度理论从序列图像重建高分辨率图像的算法——梯度解析法。该解析法根据图像灰度场梯度理论,同时考虑了图像的更高频成分,提高了重建图像分辨率。仿真实验显示,该算法与已有算法相比,重建图像的失真度降低40％以上。     

ISAR imaging of manoeuvring targets with the range instantaneous chirp rate technique

The conventional range instantaneous Doppler (RID) algorithm is a well accepted inverse synthetic aperture radar (ISAR) imaging method for manoeuvring targets. In the RID imaging, the cross-range resolution depends on the instantaneous Doppler of scatterers at the imaging instant. For a high manoeuvring target, the instantaneous Doppler of scatterers may be small at some imaging instants and the satisfactory RID images may not be obtained. On the other hand, a large instantaneous chirp rate is often present for the same scatterer at the same instant for RID imaging. In order to obtain some additional information of a manoeuvring target, a novel ISAR imaging approach, referred to as the range instantaneous chirp (RIC), is proposed based on instantaneous chirp rate of scatterer to provide cross-range resolution. Using the proposed imaging algorithm, with the same received data of RID, a RIC image is generated at the same instant with a different `view`. Therefore the RIC image may provide some additional information that is not shown in the RID image. With both the RIC and RID images, a better target recognition and identification can be achieved for high-manoeuvring targets. The proposed RIC algorithm is verified by raw radar data.     

Optimal data acquisition in fMRI using prolate spheroidal wave functions

Functional magnetic resonance imaging (fMRI) is a technique that can be used to noninvasively study mental activity in a persons brain. fMRI has the potential to answer many interesting questions regarding the way the brain functions. Unfortunately, the drawback to fMRI studies, as they are traditionally performed, is that the temporal resolution is too low to effectively answer questions regarding what happens in an active region of the brain immediately following stimulation. Shepp and Zhang ( 2000 ) introduced a new method that could potentially lead to a significant increase in temporal resolution. Their method suggests a way to improve the time resolution in fMRI studies by sampling only a fraction of the points needed to recreate a full image. Instead of full image reconstruction, an optimal prolate spheroidal wave function filter is used to obtain a measurement over the total activity in a predefined region in the brain, B , at successive time points. The sampling region and filter are chosen in order to minimize the energy loss over the region of interest (ROI). The region they suggested to sample was chosen heuristically and corresponds to the scaled polar set of B . It was shown to be near optimal through extensive computer searches. In this article the optimal sampling region is found for the case when the ROI is circular or spherical and the sampling size is small. Based on this result, a new heuristic is introduced for other ROIs, which improves upon the results obtained using the polar set of B . © 2003 Wiley Periodicals, Inc. Int J Imaging Syst Technol 13, 126–132, 2003; Published online in Wiley Inter‐Science (www.interscience.wiley.com). DOI 10.1002/ima.10051     

Analysis of computed tomographic imaging spectrometers. I. Spatial and spectral resolution

Computed tomographic imaging spectrometers measure the spectrally resolved image of an object scene in an entirely different manner from traditional whisk-broom or push-broom systems, and thus their noise behavior and data artifacts are unfamiliar. We review computed tomographic imaging spectrometry (CTIS) measurement systems and analyze their performance, with the aim of providing a vocabulary for discussing resolution in CTIS instruments, by illustrating the artifacts present in their reconstructed data and contributing a rule-of-thumb measure of their spectral resolution. We also show how the data reconstruction speed can be improved, at no cost in reconstruction quality, by ignoring redundant projections within the measured raw images.     

Adjustable active optical low-pass filter

This paper presents an active optical low-pass filter (AOLPF) capable of changing the resolution of an imaging system on demand in order to remove aliasing noise from a sampling image. This is advantageous over conventional optical low-pass filters, which are fixed image-blurring optical components that are built into the imaging system, in order to remove aliasing in the image. Furthermore, conventional filters smear images regardless of the presence or lack of high spatial frequency, which can exceed the Nyquist limit of the sensor. On the contrary, the proposed AOLPF can dynamically adjust the modulation transfer function of an imaging system to eliminate aliasing artifacts. In addition, this filter can be turned off in the absence of high spatial frequency to maximize resolution and prevent unnecessary blurring of the sampling image.     

Infrared image registration and high-resolution reconstructionusing multiple translationally shifted aliased video frames

Forward looking infrared (FLIR) detector arrays generally produce spatially undersampled images because the FLIR arrays cannot be made dense enough to yield a sufficiently high spatial sampling frequency. Multi-frame techniques, such as microscanning, are an effective means of reducing aliasing and increasing resolution in images produced by staring imaging systems. These techniques involve interlacing a set of image frames that have been shifted with respect to each other during acquisition. The FLIR system is mounted on a moving platform, such as an aircraft, and the vibrations associated with the platform are used to generate the shifts. Since a fixed number of image frames is required, and the shifts are random, the acquired frames will not fall on a uniformly spaced grid. Furthermore, some of the acquired frames may have almost similar shifts thus making them unusable for high-resolution image reconstruction. In this paper, we utilize a gradient-based registration algorithm to estimate the shifts between the acquired frames and then use a weighted nearest-neighbor approach for placing the frames onto a uniform grid to form a final high-resolution image. Blurring by the detector and optics of the imaging system limits the increase in image resolution when microscanning is attempted at sub-pixel movements of less than half the detector width. We resolve this difficulty by the application of the Wiener filter, designed using the modulation transfer function (MTF) of the imaging system, to the high-resolution image. Simulation and experimental results are presented to verify the effectiveness of the proposed technique. The techniques proposed herein are significantly faster than alternate techniques, and are found to be especially suitable for real-time applications     

A study of synthetic-aperture imaging with virtual source elements in B-mode ultrasound imaging systems

We propose an all point transmit and receive focusing method based on transmit synthetic focusing combined with receive dynamic focusing in a linear array transducer. In the method, on transmit, a virtual source element is assumed to be located at the transmit focal depth of conventional B-mode imaging systems, and transmit synthetic focusing is used in two half planes, one before and the other after the transmit focal depth, using the RF data of each scanline, together with all other relevant RF scanline data previously stored. The proposed new method uses the same data acquisition scheme as the conventional focusing method while maintaining the same frame rate via high-speed signal processing, but it is not suitable for imaging moving objects. It improves upon the lateral resolution and sidelobe level at all imaging depths. Also, it increases the transmit power and image signal-to-noise ratio (SNR), due to transmit field synthesis, and extends the image penetration depth as well. Evaluations with simulation and experimental data show much improvement in resolution and SNR at all imaging depths.     

Limited-angle spatial compound imaging of skin with high-frequency ultrasound (20 MHz)

In dermatology, high-frequency ultrasound (HFUS) is used for high-resolution skin imaging. The conventional B-scan type approach is to perform lateral scans perpendicular to the direction of sound propagation. Ultrasound spatial compounding enables improvement of the image contrast, suppression of speckle and noise, and reduction of imaging artifacts in comparison with conventional B-mode imaging, but it has not yet found its way into HFUS skin imaging applications. In this paper, the potential of HFUS spatial compounding for skin imaging is systematically evaluated. A new HFUS system with a sophisticated scanner for limited-angle (up to +/-40 degrees) spatial compound imaging was developed and implemented. Echo signals are acquired using a 20 MHz spherically focused single-element transducer with an axial and lateral resolution of 69 mum and 165 mum, respectively, in the focus. A calibration scheme for the estimation of unknown system parameters and precise image reconstruction has been developed. The implemented system has been evaluated using measurements of geometrically well-defined structures, speckle phantoms, and in vivo measurements. The results show the advantage of the proposed spatial compound skin imaging concept compared with conventional B-mode imaging in terms of image contrast, isotropy, and independence from the orientation of surfaces.     

Neural network-based image reconstruction for positron emission tomography

Positron emission tomography (PET) is one of the key molecular imaging modalities in medicine and biology. Penalized iterative image reconstruction algorithms frequently used in PET are based on maximum-likelihood (ML) and maximum a posterior (MAP) estimation techniques. The ML algorithm produces noisy artifacts whereas the MAP algorithm eliminates noisy artifacts by utilizing availableprior information in the reconstruction process. The MAP-based algorithms fail to determine the density class in the reconstructed image and hence penalize the pixels irrespective of the density class and irrespective of the strength of interaction between the nearest neighbors. A Hebbian neural learning scheme is proposed to model the nature of interpixel interaction to reconstruct artifact-free edge preserving reconstruction. A key motivation of the proposed approach is to avoid oversmoothing across edges that is often the case with MAP algorithms. It is assumed that local correlation plays a significant role in PET image reconstruction, and proper modeling of correlation weight (which defines the strength of interpixel interaction) is essential to generate artifact-free reconstruction. The Hebbian learning-based approach modifies the interaction weight by adding a small correction that is proportional to the product of the input signal (neighborhood pixels) and output signal. Quantitative analysis shows that the Hebbian learning-based adaptive weight adjustment approach is capable of producing better reconstructed images compared with those reconstructed by conventional ML and MAP-based algorithms in PET image reconstruction.     

Single-shot full resolution region-of-interest (ROI) reconstruction in image plane digital holographic microscopy

We describe a numerical processing technique that allows single-shot region-of-interest (ROI) reconstruction in image plane digital holographic microscopy with full pixel resolution. The ROI reconstruction is modelled as an optimization problem where the cost function to be minimized consists of an L2-norm squared data fitting term and a modified Huber penalty term that are minimized alternately in an adaptive fashion. The technique can provide full pixel resolution complex-valued images of the selected ROI which is not possible to achieve with the commonly used Fourier transform method. The technique can facilitate holographic reconstruction of individual cells of interest from a large field-of-view digital holographic microscopy data. The complementary phase information in addition to the usual absorption information already available in the form of bright field microscopy can make the methodology attractive to the biomedical user community.     

Efficient direct computation of the pseudo-inverse and its gradient

The pseudo-inverse (also called the Moore–Penrose inverse or the generalized inverse) has many uses in engineering in fields such as control design, structural dynamics and identification. Efficient computation of the pseudo-inverse can greatly ease the computational burden associated with these techniques. In addition, the gradient of the pseudo-inverse may be needed for sensitivity analysis or optimization. Typical methods for computing the pseudo-inverse require the singular value or eigenvalue decomposition of the appropriate matrices. Moreover, if the gradient is required, it is either computed with finite differences, or by taking the gradient of the Singular Value Decomposition (SVD) and eigen decomposition of the appropriate matrices. However, this is a very difficult task, if possible at all. This paper develops a direct method of computing the gradient of the pseudo-inverse of well-conditioned systems with respect to a scalar. The paper begins by revisiting a direct method for computing the pseudo-inverse developed by Greville for matrices with independent columns. When applied to a square, fully populated, non-symmetric case, with independent columns, it was found that the approach can be up to 8 times faster than the conventional approach of using the SVD. Rectangular cases are shown to yield similar levels of speed increase. A method is then presented which is a direct approach for computing the gradient of the pseudo-inverse that previously did not exist. To help illustrate the algorithms, simple MATLAB code is provided. © 1997 John Wiley & Sons, Ltd.     

Coherent array imaging using phased subarrays. Part II: simulations and experimental results

The basic principles and theory of phased subarray (PSA) imaging imaging provides the flexibility of reducing the number of front-end hardware channels between that of classical synthetic aperture (CSA) imaging--which uses only one element per firing event--and full-phased array (FPA) imaging-which uses all elements for each firing. The performance of PSA generally ranges between that obtained by CSA and FPA using the same array, and depends on the amount of hardware complexity reduction. For the work described in this paper, we performed FPA, CSA, and PSA imaging of a resolution phantom using both simulated and experimental data from a 3-MHz, 3.2-cm, 128-element capacitive micromachined ultrasound transducer (CMUT) array. The simulated system point responses in the spatial and frequency domains are presented as a means of studying the effects of signal bandwidth, reconstruction filter size, and subsampling rate on the PSA system performance. The PSA and FPA sector-scanned images were reconstructed using the wideband experimental data with 80% fractional bandwidth, with seven 32-element subarrays used for PSA imaging. The measurements on the experimental sector images indicate that, at the transmit focal zone, the PSA method provides a 10% improvement in the 6-dB lateral resolution, and the axial point resolution of PSA imaging is identical to that of FPA imaging. The signal-to-noise ratio (SNR) of PSA image was 58.3 dB, 4.9 dB below that of the FPA image, and the contrast-to-noise ratio (CNR) is reduced by 10%. The simulated and experimental test results presented in this paper validate theoretical expectations and illustrate the flexibility of PSA imaging as a way to exchange SNR and frame rate for simplified front-end hardware.     

Upscaling image resolution of compact imaging systems using wavefront coding and a property of the point-spread function

We propose an image-resolution upscaling method for compact imaging systems. The image resolution is calculated using the resolving power of the optics and the pixel size of a digital image sensor. The resolution limit of the compact imaging system comes from its size and the number of allowed lenses. To upscale the image resolution but maintain the small size, we apply wavefront coding and image restoration. Conventional image restoration could not enhance the image resolution of the sensor. Here, we use the upscaled image of a wavefront-coded optical system and apply an image-restoration algorithm using a more precisely calculated point-spread function (PSF) as the deconvolution filter. An example of a wavefront-coded optical system with a 5-megapixel image sensor is given. The final image had a resolution equivalent to that of a 10-megapixel image using only four plastic lenses. Moreover, image degradation caused by hand motion could also be reduced using the proposed method.     

Ultrasound synthetic aperture imaging: monostatic approach

An ultrasound synthetic aperture imaging method based on a monostatic approach was studied experimentally. The proposed synthetic aperture method offers good dynamical resolution along with fast numerical reconstruction. In this study complex object data were recorded coherently in a two-dimensional hologram using a 3.5 MHz single transducer with a fairly wide-angle beam. Image reconstruction which applies the wavefront backward propagation method and the near-field curvature compensation was performed numerically in a microcomputer using the spatial frequency domain. This approach allows an efficient use of the FFT-algorithms. Because of the simple and fast scanning scheme and the efficient reconstruction algorithms the method can be made real-time. The image quality of the proposed method was studied by evaluating the spatial and dynamical resolution in a waterbath and in a typical tissue-mimicking phantom. The lateral as well as the range resolution (-6 dB) were approximately 1 mm in the depth range of 30-100 mm. The dynamical resolution could be improved considerably when the beam width was made narrower. Although it resulted in a slightly reduced spatial resolution this compromise has to be done for better resolution of low-contrast targets such as cysts. The study showed that cysts as small as 2 mm by diameter could be resolved     

Optical architectures for compressive imaging

We compare three optical architectures for compressive imaging: sequential, parallel, and photon sharing. Each of these architectures is analyzed using two different types of projection: (a) principal component projections and (b) pseudo-random projections. Both linear and nonlinear reconstruction methods are studied. The performance of each architecture-projection combination is quantified in terms of reconstructed image quality as a function of measurement noise strength. Using a linear reconstruction operator we find that in all cases of (a) there is a measurement noise level above which compressive imaging is superior to conventional imaging. Normalized by the average object pixel brightness, these threshold noise standard deviations are 6.4, 4.9, and 2.1 for the sequential, parallel, and photon sharing architectures, respectively. We also find that conventional imaging outperforms compressive imaging using pseudo-random projections when linear reconstruction is employed. In all cases the photon sharing architecture is found to be more photon-efficient than the other two optical implementations and thus offers the highest performance among all compressive methods studied here. For example, with principal component projections and a linear reconstruction operator, the photon sharing architecture provides at least 17.6% less reconstruction error than either of the other two architectures for a noise strength of 1.6 times the average object pixel brightness. We also demonstrate that nonlinear reconstruction methods can offer additional performance improvements to all architectures for small values of noise.     

A fast and high frame rate adaptive beamforming using DCT-based RF-line recovery in line-by-line ultrasound imaging

Ultrasound imaging is an important modality used in medical imaging. One of the significant stages in the ultrasound imaging is the beamforming process. This article proposes a new technique for reducing the overall computational time of adaptive linear ultrasound imaging. The method uses the discrete cosine transform-based reconstruction for missing data imputation. The novelty of the paper is that we do not need to beam-form the total scan lines, so the time of image construction can be saved significantly. In other words, a fraction of the total scan lines is selected for beamforming and the others are assumed to have values as Not-a-Number (NaN). The proposed reconstruction technique tries to assign appropriate values to the NaN ones. We applied the proposed method to the simulated and experimental radio frequency (RF) datasets for resolution and contrast evaluation. Results showed that the proposed technique is near to the minimum variance (MV) method in terms of resolution and contrast, and has less computational time for image formation compared to the MV. As some quantitative examples in some experiments we have formed only 50% and 33% of the total lines and reconstructed the rest, then we have been able to increase the frame rate twice and three times, respectively, which can be very useful in many applications, especially in echocardiography imaging. In addition, since the execution time of the reconstruction algorithm is not very significant, we were also able to increase the speed by two and three times while achieving an error of less than 10% compared to the case of using all image lines.     

Efficient synthetic aperture imaging from a circular aperture with possible application to catheter-based imaging

Phased-array imaging, including complete dynamic focus, is explored for imaging using a circular aperture. Based on the constraints of catheter-based systems, an efficient synthetic aperture method has been developed for imaging using a single wire connection between the imaging array and external electronics. The method employs a highly sampled array with an element pitch small compared to the acoustic wavelength. On any given firing of the array, however, a large number of channels are electrically connected on both transmission and reception. From firing to firing, one element is dropped and one new element is included, in analogy to a classic linear array system. Using an optimal filtering approach for synthetic aperture reconstruction, a dynamically focused image exhibiting diffraction limited resolution is produced. The results of detailed simulations are presented demonstrating the capabilities of the method. In addition, the prospects for real-time implementation of the reconstruction are discussed.