Terahertz Imaging of Three-Dimensional Dehydrated Breast Cancer Tumors

This work presents the application of terahertz imaging to three-dimensional formalin-fixed, paraffin-embedded human breast cancer tumors. The results demonstrate the capability of terahertz for in-depth scanning to produce cross section images without the need to slice the tumor. Samples of tumors excised from women diagnosed with infiltrating ductal carcinoma and lobular carcinoma are investigated using a pulsed terahertz time domain imaging system. A time of flight estimation is used to obtain vertical and horizontal cross section images of tumor tissues embedded in paraffin block. Strong agreement is shown comparing the terahertz images obtained by electronically scanning the tumor in-depth in comparison with histopathology images. The detection of cancer tissue inside the block is found to be accurate to depths over 1 mm. Image processing techniques are applied to provide improved contrast and automation of the obtained terahertz images. In particular, unsharp masking and edge detection methods are found to be most effective for three-dimensional block imaging.     

小鼠在体皮下乳腺癌的太赫兹波成像检测研究

乳腺癌是女性常见癌症之一,乳腺癌区域的精准检测对乳腺癌的治疗有至关重要的作用。本文采用频率为2.52THz的连续太赫兹波反射式成像系统,对小鼠在体皮下乳腺癌模型进行了太赫兹波成像检测。研究结果表明,太赫兹波成像可以清晰识别出乳腺癌区域,且与肉眼可见肿瘤区域一致。在体乳腺癌区域的太赫兹波相对反射率高于正常组织,两者相对反射率差值高达15%。进一步,对距离皮肤表面不同深度的离体乳腺癌组织进行切片和苏木精-伊红(H&E)染色,作为金标准对照。结果发现乳腺癌区域的面积随着距离皮肤表面深度的增加而增大。通过将太赫兹波成像与H&E染色结果对比可知,在距离皮肤表面约460μm处,太赫兹波图像和H&E染色图中的肿瘤区域面积相等。由此可知,太赫兹波对在体皮下乳腺癌的探测深度大约在460μm左右,太赫兹波有望实现深部肿瘤的检测。     

Elimination of Fresnel Reflection Boundary Effects and Beam Steering in Pulsed Terahertz Computed Tomography

For the past few decades there has been tremendous innovation and development of Terahertz (THz) science and imaging. In particular, the technique of 3-D computed tomography has been adapted from the X-Ray to the THz range. However, the finite refractive index of materials in the THz range can severally refract probing THz beams during the acquisition of tomography data. Due to Fresnel reflection power losses at the boundaries as well as steering of the THz beam through the sample, refractive effects lead to anomalously high local attenuation coefficients near the material boundaries of a reconstructed image. These boundary phenomena can dominate the reconstructed THz-CT images making it difficult to distinguish structural defect(s) inside the material. In this paper an algorithm has been developed to remove the effects of refraction in THz-CT reconstructed images. The algorithm is successfully implemented on cylindrical shaped objects.     

Confocal microwave imaging for breast cancer detection: delay-multiply-and-sum image reconstruction algorithm

A new image reconstruction algorithm, termed as delay-multiply-and-sum (DMAS), for breast cancer detection using an ultra-wideband confocal microwave imaging technique is proposed. In DMAS algorithm, the backscattered signals received from numerical breast phantoms simulated using the finite-difference time-domain method are time shifted, multiplied in pair, and the products are summed to form a synthetic focal point. The effectiveness of the DMAS algorithm is shown by applying it to backscattered signals received from a variety of numerical breast phantoms. The reconstructed images illustrate improvement in identification of embedded malignant tumors over the delay-and-sum algorithm. Successful detection and localization of tumors as small as 2 mm in diameter are also demonstrated.     

改进的均值滤波算法在太赫兹成像中的应用

研究被动太赫兹图像的降噪算法,提出了一种改进的均值滤波算法,在原有均值滤波算法的基础上加入了阈值的概念,由被动太赫兹扫描成像的技术特点确定了滤波模块的形状,并根据图像评价参数信息熵确定了滤波模板的最佳尺寸。实验表明该算法对于被动太赫兹图像具有良好的降噪效果,可以在保留成像目标信息的基础上滤除图像背景中的噪声。该算法提高了图像质量,增加了对隐匿物的辨别能力,从而为被动太赫兹成像技术在安检工作中的应用提供了必要的保证。     

Nonrigid registration of 3-D free-hand ultrasound images of the breast

Three-dimensional (3-D) ultrasound imaging of the breast enables better assessment of diseases than conventional two-dimensional (2-D) imaging. Free-hand techniques are often used for generating 3-D data from a sequence of 2-D slice images. However, the breast deforms substantially during scanning because it is composed primarily of soft tissue. This often causes tissue mis-registration in spatial compounding of multiple scan sweeps. To overcome this problem, in this paper, instead of introducing additional constraints on scanning conditions, we use image processing techniques. We present a fully automatic algorithm for 3-D nonlinear registration of free-hand ultrasound data. It uses a block matching scheme and local statistics to estimate local tissue deformation. A Bayesian regularization method is applied to the sample displacement field. The final deformation field is obtained by fitting a B-spline approximating mesh to the sample displacement field. Registration accuracy is evaluated using phantom data and similar registration errors are achieved with (0.19 mm) and without (0.16 mm) gaps in the data. Experimental results show that registration is crucial in spatial compounding of different sweeps. The execution time of the method on moderate hardware is sufficiently fast for fairly large research studies.     

基于控制点的人脸图像绘制

基于图像的绘制变形技术已成为当前图形学的一个新的研究热点。本文介绍了图像变形和视图变形技术,由Field Morphing方法的基础上,提出了基于控制点的图像变形算法,给出实现变形的原理和步骤。通过实拍人脸图像进行了人脸局部和整体变形实验,其变形结果过渡自然,效果较好,且算法过程简洁,因此具有较好的实用性。视图变形是在图像变形中对物体形状、颜色变形的基础上添加视点变换的一种方法,本文在图像变形的基础上,提出了利用控制点的改进算法,编程实现,中间过渡图像自然逼真。     

A confocal microwave imaging algorithm for breast cancer detection

We present a computationally efficient and robust image reconstruction algorithm for breast cancer detection using an ultrawideband confocal microwave imaging system. To test the efficacy of this approach, we have developed a two-dimensional (2-D) anatomically realistic MRI-derived FDTD model of the cancerous breast. The image reconstruction algorithm is applied to FDTD-computed backscatter signals, resulting in a microwave image that clearly identifies the presence and location of the malignant lesion. These simulations demonstrate the feasibility of detecting and imaging small breast tumors using this novel approach     

小波域马尔可夫随机场在THz 图像处理中的应用

目前THz 自由空间成像面临的挑战主要有大气损耗和水分吸收,辐射功率低,成像要获得高的信噪比,需要有更高功率的辐射源;数据获取时间长;图像质量仍需改善。分析了THz 成像技术的最新发展趋势及国内外发展现状。阐述了利用THz 辐射进行合成孔径成像、THz 压缩感知成像的基本原理,并对两种种成像方法形成的THz 图像的特点进行了分析。应用Wiener2,基于熵标准的ddencmp 选定小波系数阈值降噪法、Donoho 提出的小波系数阈值降噪法以及基于小波系数幅值渐近最优降噪法等图像降噪算法对THz 图像进行处理效果从均方根误差、信噪比、相关系数等方面进行了定性、定量的比较。提出将小波域马尔可夫随机场应用于THz 图像降噪中。主要完成了以下几个方面:对每个小波系数引入两个状态,一个状态对应图像的非平稳区域,如边缘;另一个状态对应图像平稳区。每个状态下的小波系数用高斯分布函数来描述,虽然每个状态下的小波系数服从高斯分布,但每个小波系数的两个状态混合模型服从非高斯分布。然后利用EM（Expectation Maximization）算法估计混合模型中的参数,采用贝叶斯准则初步确定理想图像小波系数的收缩因子。最后将小波域隐马尔可夫模型的降噪算法进行对比试验,仿真结果表明小波域隐马尔可夫模型的降噪算法更具有效性和优异性。     

Biomechanical 3-D finite element modeling of the human breast using MRI data

Breast tissue deformation modeling has recently gained considerable interest in various medical applications. A biomechanical model of the breast is presented using a finite element (FE) formulation. Emphasis is given to the modeling of breast tissue deformation which takes place in breast imaging procedures. The first step in implementing the FE modeling (FEM) procedure is mesh generation. For objects with irregular and complex geometries such as the breast, this step is one of the most difficult and tedious tasks. For FE mesh generation, two automated methods are presented which process MRI breast images to create a patient-specific mesh. The main components of the breast are adipose, fibroglandular and skin tissues. For modeling the adipose and fibroglandular tissues, we used eight noded hexahedral elements with hyperelastic properties, while for the skin, we chose four noded hyperelastic membrane elements. For model validation, an MR image of an agarose phantom was acquired and corresponding FE meshes were created. Based on assigned elasticity parameters, a numerical experiment was performed using the FE meshes, and good results were obtained. The model was also applied to a breast image registration problem of a volunteer's breast. Although qualitatively reasonable, further work is required to validate the results quantitatively.     

Noise estimation in infrared image sequences: a tool for the quantitative evaluation of the effectiveness of registration algorithms

Dynamic infrared imaging has been proposed in literature as an adjunctive technique to mammography in breast cancer diagnosis. It is based on the acquisition of hundreds of consecutive thermal images with a frame rate ranging from 50 to 200 frames/s, followed by the harmonic analysis of temperature time series at each image pixel. However, the temperature fluctuation due to blood perfusion, which is the signal of interest, is small compared to the signal fluctuation due to subject movements. Hence, before extracting the time series describing temperature fluctuations, it is fundamental to realign the thermal images to attenuate motion artifacts. In this paper, we describe a method for the quantitative evaluation of any kind of feature-based registration algorithm on thermal image sequences, provided that an estimation of local velocities of reference points on the skin is available. As an example of evaluation of a registration algorithm, we report the evaluation of the SNR improvement obtained by applying a nonrigid piecewise linear algorithm.     

离轴抛物面镜像面扫描太赫兹光学设计

为了提高太赫兹成像速度,设计了一种像面扫描太赫兹快速成像系统。它为反射式单像素探测器成像,成像系统采用新设计的表面镀金的离轴抛物面镜结构以实现大口径、无遮拦、高反射率、高质量成像;反射成像系统光学设计F数为2.93,通光孔径为100 mm,视场为1,焦距为293.45 mm,成像窗尺寸为64 mm64 mm,圆孔直径为2 mm,扫描采集1616像素图像时间为0.1 min,3232像素图像时间为0.42 min,6464像素图像时间为1.7 min,空间分辨率为1 cm。扫描系统结合压缩传感成像理论采用新型像面扫描方法实现快速成像,在系统焦平面位置加入旋转多孔盘,对像面的图像进行太赫兹能量强度扫描,使用金属光锥收集能量到高莱探测器。利用压缩传感理论的特殊条件（采样数目与图像像素数相等）进行像面图像采集,然后利用正则归一化方程重构像面图像,该系统具有成像速度快、分辨率高、低成本、结构紧凑合理的优点。     

Not your mother's mammography [breast cancer detection]

Breast cancer accounts for nearly one of every three cancers diagnosed in US women. While great strides have been made in early detection, the conventional method of mammography is not failproof it has trouble imaging dense tissue, it may show suspicious areas where no malignancy exists, and radiologists interpreting the images can miss up to 15 percent of cancers. It's also uncomfortable, requiring each breast to be compressed between plastic plates, which can lead to bruising. Susan Hagness wants to change all that. An assistant professor of electrical engineering at the University of Wisconsin-Madison, she is pioneering a novel detection technique that uses ultrawideband microwaves to image even the tiniest malignant tumors in the breast. Breast tumors and normal tissue show much more contrast at microwave frequencies than at the X-ray frequencies used for mammograms. Microwaves are also nonionizing, and the technique requires no breast compression. In Susan Hagness' search for a better way to detect breast cancer, she gets her students involved, too. Such efforts have paid off: her courses consistently receive high marks on student evaluations.     

Nonactive antenna compensation for fixed-array microwave imaging.II. Imaging results

Model-based imaging techniques utilizing microwave signal illumination rely heavily on the ability to accurately represent the wave propagation with a suitable numerical model. To date, the highest quality images from our prototype system have been achieved utilizing a single transmitter/single receiver measurement system where both antennas are manually repositioned to facilitate multiple illuminations of the imaging region, thus requiring long data acquisition times. In an effort to develop a system that can acquire data in a real time manner, a 32-channel network has been fabricated with all ports capable of being electronically selected for either transmit or receive mode. The presence of a complete array of antenna elements at data collection time perturbs the field distributions being measured, which can subsequently degrade the image reconstruction due to increased data-model mismatch. Incorporating the nonactive antenna-compensation model from Part I of this paper into our hybrid element near field image reconstruction algorithm is shown to restore image quality when fixed antenna-array data acquisition is used. Improvements are most dramatic for inclusions located in near proximity to the antenna array itself, although cases of improvement in the recovery of centered heterogeneities are also illustrated. Increases in the frequency of illumination are found to warrant an increased need for nonactive antenna compensation. Quantitative measures of recovered inclusion shape and position reveal a systematic improvement in image reconstruction quality when the nonactive antenna-compensation model is employed. Improvements in electrical property value recovery of localized heterogeneities are also observed. Image reconstructions in freshly excised breast tissue illustrate the applicability of the approach when used with our two-dimensional microwave imaging system.     

提高0.14 THz 雷达成像质量的新方法

目前,国际上多个科研小组相继开展了太赫兹逆散射成像方面的研究,已开发出多个太赫兹逆散射成像系统。其电磁散射模型及成像处理方式多借鉴于其他辐射源已经成熟的研究成果,例如:雷达目标散射中心模型及ISAR/SAR, Born/Rytov 近似模型及层析成像。但上述方法直接应用于太赫兹波段将导致成像质量的下降。首先简要介绍了太赫兹雷达成像和太赫兹层析成像之间的关系,在分析两种成像方法特点的基础上,重点研究了大孔径、大带宽条件下的太赫兹逆散射成像,提出了一种基于Range-Doppler 算法的改进成像方法。最后,利用该方法对中物院研制的0.14 THz 雷达样机实验数据进行成像,并给出了典型目标的成像结果,验证了新成像方法的有效性。     

Terahertz composite imaging method

In order to improve the imaging quality of terahertz(THz) spectroscopy, Terahertz Composite Imaging Method(TCIM) is proposed. The traditional methods of improving THz spectroscopy image quality are mainly from the aspects of de-noising and image enhancement. TCIM breaks through this limitation. A set of images, reconstructed in a single data collection, can be utilized to construct two kinds of composite images. One algorithm, called Function Superposition Imaging Algorithm(FSIA), is to construct a new gray image utilizing multiple gray images through a certain function. The features of the Region Of Interest (ROI) are more obvious after operating, and it has capability of merging ROIs in multiple images. The other, called Multi-characteristics Pseudo-color Imaging Algorithm(McPcIA), is to construct a pseudo-color image by combining multiple reconstructed gray images in a single data collection. The features of ROI are enhanced by color differences. Two algorithms can not only improve the contrast of ROIs, but also increase the amount of information resulting in analysis convenience. The experimental results show that TCIM is a simple and effective tool for THz spectroscopy image analysis.     

Microwave imaging via space-time beamforming for early detection of breast cancer

A method of microwave imaging via space-time (MIST) beamforming is proposed for detecting early-stage breast cancer. An array of antennas is located near the surface of the breast and an ultrawideband (UWB) signal is transmitted sequentially from each antenna. The received backscattered signals are passed through a space-time beamformer that is designed to image backscattered signal energy as a function of location. The beamformer spatially focuses the backscattered signals to discriminate against clutter and noise while compensating for frequency-dependent propagation effects. As a consequence of the significant dielectric-properties contrast between normal and malignant tissue, localized regions of large backscatter energy levels in the image correspond to malignant tumors. A data-adaptive algorithm for removing artifacts in the received signals due to backscatter from the skin-breast interface is also presented. The effectiveness of these algorithms is demonstrated using a variety of numerical breast phantoms based on anatomically realistic MRI-derived FDTD models of the breast. Very small (2 mm) malignant tumors embedded within the complex fibroglandular structure of the breast are easily detected above the background clutter. The MIST approach is shown to offer significant improvement in performance over previous UWB microwave breast cancer detection techniques based on simpler focusing schemes.     

High Speed Terahertz Pulse Imaging in the Reflection Geometry and Image Quality Enhancement by Digital Image Processing

We describe the formation and enhancement of two dimensional pulsed terahertz (THz) images obtained in the reflection geometry with a high-speed optical delay line. Two test objects are imaged and analyzed with respect to material information and concealed structure. Clear THz images were obtained with various imaging modes and were compared with the X-ray images. The THz image of a sample revealed material features that the X-ray image cannot distinguish. We could enhance the THz image quality using various image processing techniques, such as edge detection, de-noising, high-pass filtering, and wavelet filtering.     

Robust segmentation of overlapping cells in histopathology specimens using parallel seed detection and repulsive level set

Automated image analysis of histopathology specimens could potentially provide support for early detection and improved characterization of breast cancer. Automated segmentation of the cells comprising imaged tissue microarrays (TMAs) is a prerequisite for any subsequent quantitative analysis. Unfortunately, crowding and overlapping of cells present significant challenges for most traditional segmentation algorithms. In this paper, we propose a novel algorithm that can reliably separate touching cells in hematoxylin-stained breast TMA specimens that have been acquired using a standard RGB camera. The algorithm is composed of two steps. It begins with a fast, reliable object center localization approach that utilizes single-path voting followed by mean-shift clustering. Next, the contour of each cell is obtained using a level set algorithm based on an interactive model. We compared the experimental results with those reported in the most current literature. Finally, performance was evaluated by comparing the pixel-wise accuracy provided by human experts with that produced by the new automated segmentation algorithm. The method was systematically tested on 234 image patches exhibiting dense overlap and containing more than 2200 cells. It was also tested on whole slide images including blood smears and TMAs containing thousands of cells. Since the voting step of the seed detection algorithm is well suited for parallelization, a parallel version of the algorithm was implemented using graphic processing units (GPU) that resulted in significant speedup over the C/C++ implementation.     

Noninvasive imaging of bioimpedance distribution by means of current reconstruction magnetic resonance electrical impedance tomography

We have developed a novel magnetic resonance electrical impedance tomography (MREIT) algorithm-current reconstruction MREIT algorithm-for noninvasive imaging of electrical impedance distribution of a biological system using only one component of magnetic flux density. The newly proposed algorithm uses the inverse of Biot-Savart Law to reconstruct the current density distribution, and then, uses a modified J-substitution algorithm to reconstruct the conductivity image. A series of computer simulations has been conducted to evaluate the performance of the proposed current reconstruction MREIT algorithm with simulation settings for breast cancer imaging applications, with consideration of measurement noise, current injection strength, size of simulated tumors, spatial resolution, and position dependency. The present simulation results are highly promising, demonstrating the high spatial resolution, high accuracy in conductivity reconstruction, and robustness against noise of the proposed algorithm for imaging electrical impedance of a biological system. The present MREIT method may have potential applications to breast cancer imaging and imaging of other organs.