Contrast imaging with chirped excitation

Coded excitation has been successfully used in imaging to increase the signal-to-noise ratio (SNR) and penetration depth. With a contrast agent, wideband signals have been hypothesized to increase the contrast-to-tissue ratio (CTR). However, nonlinear properties of contrast agents make decoding difficult when applying coded excitation to contrast imaging. We propose two chirped excitation methods to image contrast agents, with a mechanical index (MI) ranging from 0.05 to 0.34. In the single chirp method, one chirp is transmitted, followed by a clutter filter to reject tissue echoes, then a matched filter is used to recover range resolution. In the chirp sequence method, an increasing and decreasing chirp sequence is transmitted followed by subtraction of the compressed echoes to reject tissue echoes (assuming tissue is a linear scatterer at low MI). Ten independent acoustic experiments were performed to evaluate the CTR for chirp and tone burst insonation, with the same spatial peak temporal averaged intensity (I(SPTA)). A significant increase in CTR, ranging from 4 dB to 8 dB, is observed for chirped excitation as compared with tone burst insonation, at an I(SPTA) of 0.1 and 0.3 mW/cm2 (P < or = 5e-3). To achieve the same CTR of 15 dB, the spatial peak pulse averaged intensity (I(SPPA)) can be decreased by 6 dB for chirp insonation as compared with tone burst insonation (P < 1e-5). Additionally, an increase of more than 10 dB in tissue rejection ratio (TRR) is observed for a chirp sequence insonation compared to tone burst phase inversion for this set of parameters (P < or = 1e-9). Deconvolution of the linear microbubble response from the received echoes is proposed as a method to recover spatial resolution. The difference in the axial resolution resulting from chirp and three-cycle tone burst insonation is approximately 220 microm. The difference in the mainlobe width between experimental and predicted compressed echoes is less than 20%. The side-lobe amplitude is 9 dB to 16 dB below the mainlobe with a transmitted I(SPTA) from 0.1 to 6.6 mW/cm2.     

一种视频强杂波两级空域滤波抑制方法

为便于对复杂视频强杂波背景下的微弱运动目标进行检测,提出了一种两级空域滤波强杂波抑制方法。采用局域均值去除(LMR)作为一级滤波,将原始图像变换为较大局域内均值和方差缓变的二维广义平稳过程,再通过基于二维AR模型参数估计的二级滤波器自适应滤除残余杂波。实验结果表明,对于一般噪声条件下的视频目标图像,利用该方法处理后得到的残留噪声呈现出很好的高斯性和独立性,并且输出目标信号杂波噪声比(SCNR)的平均增益达到1．33dB,有利于进一步的检测。     

Sources of image degradation in fundamental and harmonic ultrasound imaging using nonlinear, full-wave simulations

A full-wave equation that describes nonlinear propagation in a heterogeneous attenuating medium is solved numerically with finite differences in the time domain (FDTD). This numerical method is used to simulate propagation of a diagnostic ultrasound pulse through a measured representation of the human abdomen with heterogeneities in speed of sound, attenuation, density, and nonlinearity. Conventional delay-andsum beamforming is used to generate point spread functions (PSF) that display the effects of these heterogeneities. For the particular imaging configuration that is modeled, these PSFs reveal that the primary source of degradation in fundamental imaging is reverberation from near-field structures. Reverberation clutter in the harmonic PSF is 26 dB higher than the fundamental PSF. An artificial medium with uniform velocity but unchanged impedance characteristics indicates that for the fundamental PSF, the primary source of degradation is phase aberration. An ultrasound image is created in silico using the same physical and algorithmic process used in an ultrasound scanner: a series of pulses are transmitted through heterogeneous scattering tissue and the received echoes are used in a delay-and-sum beamforming algorithm to generate images. These beamformed images are compared with images obtained from convolution of the PSF with a scatterer field to demonstrate that a very large portion of the PSF must be used to accurately represent the clutter observed in conventional imaging.     

An ultrasonic imaging speckle-suppression and contrast-enhancement technique by means of frequency compounding and coded excitation

A method for improving the contrast resolution of B-mode images is proposed by combining the speckle-reduction technique of frequency compounding (FC) and the codedexcitation and pulse-compression technique called resolution enhancement compression (REC). FC suppresses speckle but at the expense of a reduction in axial resolution. Using REC, the axial resolution and bandwidth of the imaging system was doubled. Therefore, by combining REC with FC (REC-FC), the tradeoff between axial resolution and contrast enhancement was extended significantly. Simulations and experimental measurements were conducted with a single-element transducer (f/2.66) having a center frequency of 2.25 MHz and a -3-dB bandwidth of 50%. Simulations and measurements of hyperechoic (+6 dB) tissue-mimicking targets were imaged. Four FC cases were evaluated: full-, half-, third-, and fourth-width of the true impulse response bandwidth. The image quality metrics used to compare REC-FC to conventional pulsing (CP) and CP-FC were contrast-to-noise ratio (CNR), speckle signal-to- noise ratio, histogram pixel intensity, and lesion signal-to-noise ratio. Increases in CNR of 121%, 231%, 302%, and 391% were obtained in experiments when comparing REC-FC for the full-, half-, third-, and fourth-width cases to CP. Furthermore, smaller increases in CNR of 112%, 233%, and 309% were obtained in experiments when comparing CP-FC for the half-, third-, and fourth-width cases to CP. Improved lesion detectability was observed by using REC-FC.     

基于神经网络和方差的快速分形图像编码算法

为克服快速分形图像编码带来的解码图像质量下降问题,提出了一种神经网络与方差混合编码的快速分形图像编码算法.该算法结合图像子块复杂度与方差值的对应关系,根据每个区块的方差值大小选择适当的映射编码方法,即对于方差值相对小的区块采用方差编码以提高编码速度,对于方差值相对大的区块采用神经网络编码以提高编码质量.该算法可以较好地修正传统分形编码中由于自仿射映射结构限制所带来的解码质量偏低的问题,在大幅提高编码速度的同时,很好地保持了图像的编码质量.实验结果表明,该算法对比基本分形编码算法可以加速24倍,解码图像的质量对比方差快速分形编码算法有1.1dB的提高.同时,该算法的硬件实现比较容易,非常贴近实用化.     

Three-stage approach to ultrasound contrast detection

A new method for detecting ultrasound contrast agents using a three-stage pulsing sequence is proposed. The method is based on observations showing that the scattering properties of contrast agents are modified by ultrasonic insonation at high power, but remain unchanged at low power. The objective of the first stage of the pulsing sequence is to use low power pulses to obtain a high resolution reference image without altering the agent. Higher power pulses in the second stage modify the contrast agent. The third stage detects the changes imposed to the contrast agent using low power pulses. A temporal filter is proposed to discriminate contrast response from clutter signal. The method is similar to power Doppler methods in that it uses several pulses to survey the target while destroying the agent. The new idea is to separate detection and destruction to circumvent a trade-off between sensitivity and resolution. Results from in vitro experiments with three different contrast agents are presented. The results are compared with harmonic power Doppler processed from the same data and show that an improvement in sensitivity is achievable by including the high power burst in the pulsing sequence. The results also show that the proposed filter reduces clutter artifacts from moving tissue     

Method for reduction of background artifacts of images in scanning holography with a Fresnel-zone-plate coded aperture

Near-infrared scanning holography with a Fresnel zone plate (FZP) coded aperture has potential applications in imaging through turbid media. However, the nonnegative intensity-distribution function of the FZP coded aperture introduces the background artifacts into the reconstructed images, reducing the contrast and the signal-to-noise ratio (SNR) of the images. A novel method termed as the composite hologram is proposed to reduce the artifacts. The computer simulations showed that the contrast and the SNR of the reconstructed images had improvements of at least 50.2% and 5.58-dB, respectively, compared with the conventional method. The composite hologram of a metal ring with a 6.0-mm diameter made by a wire with a 0.4-mm diameter immersing in 1% intralipid solution was recorded, and the reconstruction was performed numerically. The experimental results demonstrated that the contrast and the SNR of the reconstructed image had improvements of at least 32.3% and 2.51-dB, respectively.     

应用ICA滤波器技术提取图像纹理特征

针对纹理图像分类问题,本文提出了一种应用ICA滤波器技术提取图像纹理特征的方法.该方法首先从训练图像集中随机抽取图像块作为观测信号,应用ICA技术,提取滤波器组.然后根据训练样本图像对滤波器组的响应值来评估和选择滤波器组,达到降维的目的.最后利用滤波器组对测试图像进行滤波,得到该图像的滤波响应结果,从该响应结果中得到最大响应滤波器编号,提取其直方图作为图像的全局特征和局部特征.对Brodatz纹理图像集中108个纹理类别进行了分类实验,结果表明,与MPEG-7纹理描述子相比,该图像特征对纹理图像具有更好的分类效果.     

Multivariate analysis-based image enhancement model for machine vision inspection

Image enhancement is an essential procedure in machine vision-based inspection. In practical applications, image enhancement is usually a part of image pre-processing, intended to make the following inspection more effective. The image enhancement method is usually selected by trial-and-error or on the basis of experience. This paper presents an automatic procedure for fast and effective image enhancement. The procedure uses multivariate analysis to automatically construct an optimal image enhancement model. First, an optimally enhanced image was selected from the literature as a basis for the model. Then, the image features were identified and Wilks’ statistic was used for feature selection. Next, discriminate functions were built to select the optimal image enhancement method. To verify the model, 53 training images from the literature and 12 test images from a local company were used in an experimental analysis. The model achieved 98.11% accuracy in selecting the most suitable image enhancement method, and the average increase in contrast was 98% for the 53 training images. The enhancement method selection results for the 12 test images were also in agreement with the 53 training images from the literature. The results show that the proposed method is effective and appropriate for quickly improving image contrast.     

Speckle reduction in optical coherence tomography by adaptive total variation method

An adaptive total variation method based on the combination of speckle statistics and total variation restoration is proposed and developed for reducing speckle noise in optical coherence tomography (OCT) images. The statistical distribution of the speckle noise in OCT image is investigated and measured. With the measured parameters such as the mean value and variance of the speckle noise, the OCT image is restored by the adaptive total variation restoration method. The adaptive total variation restoration algorithm was applied to the OCT images of a volunteer’s hand skin, which showed effective speckle noise reduction and image quality improvement. For image quality comparison, the commonly used median filtering method was also applied to the same images to reduce the speckle noise. The measured results demonstrate the superior performance of the adaptive total variation restoration method in terms of image signal-to-noise ratio, equivalent number of looks, contrast-to-noise ratio, and mean square error.     

一种基于关联处理的声呐图像去噪技术

为了改善声呐图像中存在大量杂波而导致目标跟踪困难,设备虚警率高的缺点,提出一种图像关联降噪算法。首先利用目标特性对静止目标进行剔除,之后利用目标运动的持续性和目标回波在连续多帧图像中的空间位置关联性,对随机噪声进行进一步滤除。仿真和试验数据验证,所提出的算法对于背景比较稳定的图像,降噪效率不低于95%。     

基于凸包优化的盲源分离在图像去噪中的研究

目的针对高斯-脉冲混合噪声图像中难以有效去除大量奇异点或离群数据的问题,提出一种基于凸包优化的盲源分离方法来去除图像中的混合噪声。方法该方法把混合噪声和原图均看作未知的源信号,依据噪声图像中混合噪声与原图内容的加性关系建立盲源分离的模型,并利用凸包优化的方法构建源信号(凸包极点)的仿射包,然后通过最小化仿射包到凸包(噪声图像)上的投影误差,求解混合噪声和原图2个源信号,实现去噪混合噪声、复原原图的目的。结果实验结果发现,无论高斯-脉冲混合噪声强弱,该方法去噪复原后的峰值信噪比和平均结构相似性分别在39.9129 d B和0.9以上。结论由实验数据证实该方法可有效地从盲源分离的角度去除图像中高斯-脉冲混合噪声、复原原始图像。     

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.     

可见光图像背景起伏的平稳性和相关性分析

提出了单位根假设检验可见光图像背景起伏平稳性的方法,理论上证明了时空域变化的广义平稳性。该方法采用ADF假设检验,从时域和空域分析背景灰度的变化,利用线性回归的方法进行协整性检验,从而得出结论。在平稳的基础上,使用相关长度刻划背景起伏的时空域相关性,得到两个结论。(1)一维指数模型的时间相关长度分析表明背景起伏具有强时相关性。并且这种强相关性集中体现在像素点灰度均值和相邻的有限帧(1～2帧)。因此提出低阶AR模型(1～2阶)对这种特性进行描述,得到的模型参数可用于图像背景估计。(2)空间相关长度分析证实了背景起伏具有强的空域相关性。并且图像可以分割成若干个不相关的区域。总的来说,背景起伏具有时空域的双重平稳性和强相关性。     

Use of modulated excitation signals in medical ultrasound. Part II: Design and performance for medical imaging applications

In the first paper, the superiority of linear FM signals was shown in terms of signal-to-noise ratio and robustness to tissue attenuation. This second paper in the series of three papers on the application of coded excitation signals in medical ultrasound presents design methods of linear FM signals and mismatched filters, in order to meet the higher demands on resolution in ultrasound imaging. It is shown that for the small time-bandwidth (TB) products available in ultrasound, the rectangular spectrum approximation is not valid, which reduces the effectiveness of weighting. Additionally, the distant range sidelobes are associated with the ripples of the spectrum amplitude and, thus, cannot be removed by weighting. Ripple reduction is achieved through amplitude or phase predistortion of the transmitted signals. Mismatched filters are designed to efficiently use the available bandwidth and at the same time to be insensitive to the transducer's impulse response. With these techniques, temporal sidelobes are kept below 60 to 100 dB, image contrast is improved by reducing the energy within the sidelobe region, and axial resolution is preserved. The method is evaluated first for resolution performance and axial sidelobes through simulations with the program Field II. A coded excitation ultrasound imaging system based on a commercial scanner and a 4 MHz probe driven by coded sequences is presented and used for the clinical evaluation of the coded excitation/compression scheme. The clinical images show a significant improvement in penetration depth and contrast, while they preserve both axial and lateral resolution. At the maximum acquisition depth of 15 cm, there is an improvement of more than 10 dB in the signal-to-noise ratio of the images. The paper also presents acquired images, using complementary Golay codes, that show the deleterious effects of attenuation on binary codes when processed with a matched filter, also confirmed by presented simulated images.     

MRI brain image enhancement using brightness preserving adaptive fuzzy histogram equalization

In this article, fuzzy logic based adaptive histogram equalization (AHE) is proposed to enhance the contrast of MRI brain image. Medical image plays an important role in monitoring patient's health condition and giving an effective diagnostic. Mostly, medical images suffer from different problems such as poor contrast and noise. So it is necessary to enhance the contrast and to remove the noise in order to improve the quality of a various medical images such as CT, X‐ray, MRI, and MAMOGRAM images. Fuzzy logic is a useful tool for handling the ambiguity or uncertainty. Brightness Preserving Adaptive Fuzzy Histogram Equalization technique is proposed to improve the contrast of MRI brain images by preserving brightness. Proposed method comprises of two stages. First, fuzzy logic is applied to an input image and then it's output is given to AHE technique. This process not only preserves the mean brightness and but also improves the contrast of an image. A huge number of highly MRI brain images are taken in the proposed method. Performance of the proposed method is compared with existing methods using the parameters namely entropy, feature similarity index, and contrast improvement index and the experimental results show that the proposed method overwhelms the previous existing methods.     

Assessing and improving acoustic radiation force image quality using a 1.5-D transducer design

A 1.5-D transducer array was proposed to improve acoustic radiation force impulse (ARFI) imaging signal-to-noise ratio (SNRARFI) and image contrast relative to a conventional 1-D array. To predict performance gains from the proposed 1.5-D transducer array, an analytical model for SNRARFI upper bound was derived. The analytical model and 1.5-D ARFI array were validated using a finite element modelbased numerical simulation framework. The analytical model demonstrated good agreement with numerical results (correlation coefficient = 0.995), and simulated lesion images yielded a significant (2.92 dB; p < 0.001) improvement in contrast-tonoise ratio when rendered using the 1.5-D ARFI array.     

Towards Robust Rain Removal with Unet++

Image deraining has become a hot topic in the field of computer vision. It is the process of removing rain streaks from an image to reconstruct a high-quality background. This study aims at improving the performance of image rain streak removal and reducing the disruptive effects caused by rain. To better fit the rain removal task, an innovative image deraining method is proposed, where a kernel prediction network with Unet++ is designed and used to filter rainy images, and rainy-day images are used to estimate the pixel-level kernel for rain removal. To minimize the gap between synthetic and real data and improve the performance in real rainy image handling, a loss function and an effective data optimization method are suggested. In contrast with other methods, the loss function consists of Structural Similarity Index loss, edge loss, and L1 loss, and it is adopted to improve performance. The proposed algorithm can improve the Peak Signal-to-Noise ratio by 1.3% when compared to conventional approaches. Experimental results indicate that the proposed method can achieve a better efficiency and preserve more image structure than several classical methods.     

Multi-parameter acoustic imaging of uniform objects in inhomogeneous soft tissue

The problem studied in this paper is ultrasound image reconstruction from frequency-domain measurements of the scattered field from an object with contrast in attenuation and sound speed. The case in which the object has uniform but unknown contrast in these properties relative to the background is considered. Background clutter is taken into account in a physically realistic manner by considering an exact scattering model for randomly located small scatterers that vary in sound speed. The resulting statistical characteristics of the interference are incorporated into the imaging solution, which includes application of a total-variation minimization-based approach in which the relative effect of perturbation in sound speed to attenuation is included as a parameter. Convex optimization methods provide the basis for the reconstruction algorithm. Numerical data for inversion examples are generated by solving the discretized Lippman-Schwinger equation for the object and speckle-forming scatterers in the background. A statistical model based on the Born approximation is used for reconstruction of the object profile. Results are presented for a two-dimensional problem in terms of classification performance and compared with minimum-l2-norm reconstruction. Classification using the proposed method is shown to be robust down to a signal-to-clutter ratio of less than 1 dB.