非线性超声射频信号熵对乳腺结节良恶性的定征

本文提出了一种基于非线性超声射频(radio frequency, RF)信号熵对乳腺结节良恶性进行定征的方法.对306例乳腺结节样本(良性158例,恶性148例)提取了基于超声RF信号二次谐波的熵和加权熵,以及常规超声参数(图像灰度、纵横比、不规则度、乳腺结节大小、深度);采用t检验和线性分类器检测参数对乳腺结节良恶性的区分度;进一步将有效参数组合输入支持向量机对乳腺结节良恶性进行分类.结果表明:除图像灰度外,其余参数均在乳腺结节的良性与恶性间有显著差异.多参数结合输入支持向量机的良恶性分类的准确率、敏感性和特异性分别为81.4%, 78.4%和84.2%.本文工作表明非线性超声RF信号的熵可有效地定征乳腺结节的良恶性,有望成为乳腺结节良恶性定征新参量.     

基于NSCT和CLAHE的乳腺钼靶X线图像微钙化点增强方法

针对微钙化点容易漏检的问题,提出一种非下采样轮廓波变换结合对比度受限自适应直方图均衡的乳腺图像微钙化点增强新算法。对乳腺图像预处理,提取乳房区域并将胸肌区域去除;再对图像进行非下采样轮廓波变换提取多尺度、多方向的子带,对其中的多个高频子带采用高斯拉普拉斯算子检测边缘并增强;进一步采用对比度受限自适应直方图均衡算法,提高图像局部小区域的对比度,实现乳腺图像微钙化点增强算法。结果表明该方法是一种有效的乳腺钼靶图像微钙化点增强方法,为微钙化点检测和乳腺癌诊断提供支持。     

空域近红外光谱乳腺检测仪研制及应用

为了早期诊断和治疗女性乳腺疾病,保障女性健康,利用空间分辨近红外光谱分析技术,研制出空间分辨的近红外光谱乳腺疾病检测装置。这种装置具有检测方便、无创、无辐射、成本低等优点。对女性乳腺进行了实际检测,与医生诊断结果进行比较后发现该空域近红外光谱乳腺检测仪检测数据可靠,可作为X光成像和核磁共振成像等精确检测手段前的预检测,是一项值得推广应用的乳腺疾病早期诊断新技术。     

一种基于2D-CNN的激光超声表面缺陷检测方法

激光超声表面缺陷检测的过程中,缺陷的定量表征通常依赖于操作者的判断,易受到人为因素干扰,致使检测结果不稳定。针对这一问题,提出一种基于图像识别的二维卷积神经网络（2D-CNN）的缺陷自动分类检测方法。利用有限元方法模拟激光超声检测过程,并采集超声信号数据用于训练分类模型;使用连续小变换（CWT）处理超声信号得到小波时频图,以小波时频图作为输入训练卷积神经网络（CNN）分类模型,实现对表面缺陷深度的自动分类。验证结果表明:提出的检测方法能够对不同深度的缺陷准确分类,测试的平均准确率达到97.3%;构建的CNN分类模型能够自主学习输入图像的缺陷特征并完成分类,提高了检测结果稳定性,为激光超声缺陷检测的自动化分析处理提供了新的思路。     

利用分幅相机测量铋球表面发射X射线图像

设计了一种塑料靶表面涂铋(Bi)的靶丸替代常规内爆靶,利用分幅相机获取辐射驱动内爆替代靶丸Bi等离子体再发射X射线的2维图像。实验时,从主激光中分出一束光信号,经光电转换后作为分幅相机的触发信号,以激光直接驱动金球靶建立相机的时标。根据分幅相机的时标可确定每幅X射线图像相对于主激光的时间延迟。分析Bi球靶的X射线分幅图像,得到夹持内爆靶丸的CH膜的烧蚀时间及Bi球靶半径的变化关系。通过X射线图像还可反推出诊断孔的大小和CH膜支撑靶丸的对称性。     

基于压电探测判定激光支持燃烧波和爆轰波的点燃阈值

为了获得激光支持燃烧波和爆轰波的点燃阈值,采用压电探测器检测波长为1 064nm的Nd:YAG激光作用在铝靶表面所产生的应变和冲压。从实验结果观察到压电信号的变化分为3个阶段,分别为光热弹性应变阶段、等离子体增强耦合阶段和激光支持爆轰波对靶表面的压力阶段,并从理论上研究了这3个阶段的激光与靶材料相互作用的机理,从而可以从压电信号是否发生跃变判断出激光支持燃烧波和激光支持爆轰波的点燃阈值,与其它方法所得到结果基本吻合。     

基于压电探测判定激光支持燃烧波和爆轰波的点燃阈值

为了获得激光支持燃烧波和爆轰波的点燃阈值,采用压电探测器检测波长为1 064 nm的Nd:YAG激光作用在铝靶表面所产生的应变和冲压。从实验结果观察到压电信号的变化分为3个阶段,分别为光热弹性应变阶段、等离子体增强耦合阶段和激光支持爆轰波对靶表面的压力阶段,并从理论上研究了这3个阶段的激光与靶材料相互作用的机理,从而可以从压电信号是否发生跃变判断出激光支持燃烧波和激光支持爆轰波的点燃阈值,与其它方法所得到结果基本吻合。     

用于显示乳房局部病灶组织红外热图像的伪彩色方法

通过检测人体体表每点的红外热辐射能量,可以得到反映体表温度分布的红外热图像。当乳房内部出现恶性肿瘤时,由于局部病灶组织具有异常的血运状态,会引起乳房表面病灶区域的温度显著升高。医生通过对乳房红外热图像病灶区域进行视觉分析、判断,可以实现对乳腺癌的检测。为了便于医生更好地发现这些病灶区域,本论文通过引入视觉因素,改进了传统的伪彩色显示方法,使病灶区域具有更鲜明的显示效果。这一方法的效果在47例乳腺癌病人的乳房红外热图像上得到了证实。采用这一方法对红外热图像病灶区域进行视觉分析所得到的结果,可以和采用近红外光谱等方法得到的组织血运状态进行对照比较,从而获得更为确切的诊断信息。     

基于改进YOLO-V5深度学习模型的靶丸快速筛选方法

针对激光惯性约束核聚变实验中海量靶丸筛选效率低的问题，提出一种基于改进YOLO-v5深度学习模型的靶丸快速筛选方法。方法通过控制靶丸在不同的景深处成像，并将图像拼接在一起以获得其清晰图像；同时引入通道注意力机制来增强模型的特征提取能力，建立了SE-YOLOV5s深度学习靶丸表面缺陷识别模型，并对靶丸缺陷按照缺陷种类进行了分类和评估从而实现对海量靶丸的筛选。靶丸表面缺陷检测的准确率为94.4%,每秒可检测到约50张靶丸图像(分辨率3072×4096),为激光惯性约束核聚变试验提供一种快速、准确筛选海量靶丸的方法。     

基于分布式激光超声的带筋构件R区缺陷检测方法

针对带筋构件R区多类型缺陷的快速检测和精确识别等难题，提出基于分布式激光超声的带筋构件R区缺陷检测和分类识别方法。通过建立有限元模型研究了激光超声在带筋构件中的传播规律及其与R区表面裂纹、近表面气孔等缺陷的相互作用机理，进而设计制作了含典型人工缺陷的6061铝合金带筋构件试样，开展激光超声检测实验。实验获得的缺陷时域信号与B-scan特征图像及仿真结果一致，基于反射与衍射原理实现了对带筋构件R区缺陷定位与定量检测，从而验证了所提分布式激光超声检测方法的可行性，为带筋构件制造缺陷的快速检测和分类识别提供了新思路。     

Influence of the organism interface on the breast cancer detection by UWB

Ultra-wide band (UWB) imaging technique is very attractive for the early breast cancer detection based on the obvious contrast in the electrical properties of malignant tumor to the normal fatty breast tissue. The tumor can be detected by analyzing the reflecting and scattering behavior of the UWB microwaves propagating in the breast. In this study, the influence of the organism interfaces is investigated from different cases of breast configuration involving different gland shapes as well as the tumor locations. Results show that the gland structure and tumor status have large influences on the reconstructed images generated from the detected signals due to the interface varieties. The tumor information in the proposed configurations can be obtained by series signal processing including eliminating the early time response of the detected signals caused by the direct wave and the reflection from the interface between the skin and the breast fat, and compensating the path loss of the propagating signal due to the radial spreading and the attenuation in the lossy breast. The location and the number of emitters and detectors affect the quality of the reconstructed image.     

聚类算法用于中药材的近红外光谱分析

将近红外光谱分析技术结合聚类算法应用于中药材的鉴别分析,为当前中药材的类别分析提供了一种新的思路。选择黄樟油、桂叶油、桉叶油、松油醇、丁香叶油及三个不同来源的艾叶油共8个中药样品用实验室自行研制的多通道近红外光谱仪器进行快速(数秒钟)吸收光谱测试。以空气为本底,测试光谱范围700～1 700nm的药品透射光谱(吸光度),结果显示8个样品的光谱差异较大。对此八种近红外光谱建立了定性数学模型,然后进行了聚类分析,并选择不同的聚类方法进行优化,得到相似系数为0.974 2,表明该聚类分析可行。在聚类分析产生的聚类树中,8个样品的聚类性质与其实际特性相符良好,特别是三种艾叶油被归为最近的类中,因此该聚类分析结果合理。     

A progressive processing method for breast cancer detection via UWB based on an MRI-derived model

Ultra-wideband （UWB） microwave imaging is a promising method for breast cancer detection based on the large contrast of electric parameters between the malignant tumor and its surrounded normal breast organisms. In the case of multiple tumors being present, the conventional imaging approaches may be ineffective to detect all the tumors clearly. In this paper, a progressive processing method is proposed for detecting more than one tumor. The method is divided into three stages： primary detection, refocusing and image optimization. To test the feasibility of the approach, a numerical breast model is developed based on the realistic magnetic resonance image （MRI）. Two tumors are assumed embedded in different positions. Successful detection of a 3.6 mm-diameter tumor at a depth of 42 mm is achieved. The correct information of both tumors is shown in the reconstructed image, suggesting that the progressive processing method is promising for multi-tumor detection.     

Nonlinear analysis using Lyapunov exponents in breast thermograms to identify abnormal lesions

Breast diseases are one of the major issues in women’s health today. Early detection of breast cancer plays a significant role in reducing the mortality rate. Breast thermography is a potential early detection method which is non-invasive, non-radiating, passive, fast, painless, low cost, risk free with no contact with the body. By identifying and removing malignant tumors in early stages before they metastasize and spread to neighboring regions, cancer threats can be minimized. Cancer is often characterized as a chaotic, poorly regulated growth. Cancerous cells, tumors, and vasculature defy have irregular shapes which have potential to be described by a nonlinear dynamical system. Chaotic time series can provide the tools necessary to generate the procedures to evaluate the nonlinear system. Computing Lyapunov exponents is thus a powerful means of quantifying the degree of the chaos.In this paper, we present a novel approach using nonlinear chaotic dynamical system theory for estimating Lyapunov exponents in establishing possible difference between malignant and benign patterns. In order to develop the algorithm, the first hottest regions of breast thermal images are identified first, and then one dimensional scalar time series is obtained in terms of the distance between each subsequent boundary contour points and the center of the mass of the first hottest region. In the next step, the embedding dimension is estimated, and by time delay embedding method, the phase space is reconstructed. In the last step, the Lyapunov exponents are computed to analyze normality or abnormality of the lesions. Positive Lyapunov exponents indicates abnormality while negative Lyapunov exponents represent normality. The normalized errors show the algorithm is satisfactorily, and provide a measure of chaos. It is shown that nonlinear analysis of breast thermograms using Lyapunov exponents may potentially capable of improving reliability of thermography in breast tumor detection as well as the possibility of differentiating between different classes of breast lesions.     

近红外光谱在爆炸物粉末表面沾染遥测中的应用

针对爆炸恐怖事件预防和打击领域内的大范围开放空间下制爆运爆可疑人员衣物表面沾染爆炸物粉末检测问题,研究基于近红外光谱的爆炸物粉末表面沾染遥测方法。研制了一套近红外成像光谱数据采集系统,采集了多种爆炸物粉末和沾染基底的近红外反射光谱,制备了多个爆炸物粉末表面沾染样本。针对表面沾染检测应用中爆炸物粉末与沾染基底近红外反射特征混叠问题,利用近红外光谱数据处理技术构建近红外光谱解混校正模型,去除了沾染基底信号对爆炸物粉末目标识别的干扰。针对遥测应用中光源照射不均匀问题造成的干扰（如强光反射造成的光谱信号饱和,光线遮挡造成阴影引起的信号微弱,引起光谱反射率测量异常问题）,对目标校正得分图进行有效过滤避免误识别问题。此外,针对背景噪声较大时出现光谱预处理过度造成的误识别问题,利用目标原始光谱反射率均值和得分图综合判别加以校正解决。通过实验验证,提出的方法成功解决了表面沾染特征混叠问题、去除了遥测中光照及其他噪声因素的干扰影响,避免了误分类,在典型背景材质棉麻、化纤布料基底上成功识别分类AP（高氯酸铵）、CL-20（六硝基六氮杂异伍兹烷）、NQ（硝基胍）、RDX（黑索金）、TATB（三氨基三硝基苯）、硝娣（工业炸药）、烟花爆竹等爆炸物粉末单质及混合物,验证了系统及方法的有效性和可行性,首次在实验室环境下实现了爆炸物粉末表面沾染遥测成像报警,有效距离可达数十米,具备一定应用价值与发展潜力。     

乳腺癌检测的三维微波热声成像技术

提出了三维微波热声成像技术检测早期乳腺肿瘤,成像同时具有高对比度和高分辨率的特点.该技术利用自适应的鲁棒Capon波束成形(RCB)算法进行信号处理和图像重建.基于电磁学和声学时域有限差分(FDTD)法,进行微波热声成像仿真,算例结果证实了该技术用于诊断早期乳腺肿瘤的可行性. 关键词： 乳腺癌检测 微波热声成像 鲁棒的Capon波束成形 时域有限差分     

一种用于玉米品种鉴别的近红外光谱频率选择方法

提出了一种近红外光谱的频率选择方法用于玉米品种鉴别。首先确定一种衡量特征鉴别能力的准则函数,然后根据该准则函数逐步选出适合于分类的特征频率,并通过去除各频率特征之间的相关性使得优选出的频率特征包含尽可能多的品种类间差异信息,优先选择方差较大的频率特征以减弱噪声的影响。实验结果表明,频率选择大幅度地改善了识别效果,仅使用30维频率特征即可达到94.16%的识别率。随机模拟实验显示,优选出的频率特征的识别效果对频率的小幅随机扰动不敏感,验证了本方法的鲁棒性。     

拉曼激光雷达探测低对流层大气二氧化碳分布

介绍了中国科学院安徽光学精密机械研究所研制成功的我国第一台测量低对流层大气CO2时空分布的拉曼激光雷达系统,选用波长355nm的紫外激光作为光源,利用光子计数卡双通道采集大气中N2和CO2的拉曼后向散射信号。详细分析了拉曼激光雷达系统的定标方法,提出采用Li7500型H2O/CO2分析仪与拉曼激光雷达系统进行对比与标定,结果显示激光雷达与CO2分析仪数据变化趋势一致性较好,激光雷达具有很高的探测灵敏度与准确性,通过线性拟合水平方向标定误差小于0.2%,垂直方向小于1.4%。由标定关系反演出大气中CO2的时空分布,给出了合肥西郊低对流层大气CO2水平方向0～2.0km与垂直方向0～2.5km分布的典型测量结果。     

Computer simulation of time-resolved optical imaging of objects hidden in turbid media

We review research on time-resolved optical imaging of objects hidden in strongly scattering media, with emphasis on the application to breast cancer detection. A method is presented to simulate the propagation of light in turbid media. Based on a numerical algorithm to solve the time-dependent diffusion equation, the method takes into account spatial variations of the reduced scattering and absorption factors of the medium due to the presence of objects as well as random fluctuations of these factors. It is shown that the simulation method reproduces, without fitting, experimental results on tissue-like phantoms. Using experimental and simulation results, an assessment is made of the reliability for extracting the reduced scattering and absorption coefficients of the medium from time-resolved reflection and transillumination data. The simulation technique is employed to study the conditions for locating mm-sized objects immersed in a turbid medium, by direct, time-resolved imaging. We discuss a simple method to enhance the imaging power of the time-resolved technique. The mathematical justification of the method, as well as some applications to simple problems, is given. The simulation technique is employed to demonstrate the effectiveness of the data processing technique. Results of time-resolved reflection experiments and simulations are presented, showing that the use of the latter allow us to locate 1 mm diameter objects under conditions which would prevent detection otherwise. Our results demonstrate that the combination of simulation and the appropriate processing of the diffusive part of the time-resolved reflected or transmitted light intensity may substantially increase the potential of the time-resolved near-infrared diffusive light imaging technique as a diagnostic tool for breast cancer detection.     

Breast disease evaluation with fat-suppressed magnetic resonance imaging.

Thirty patients with a variety of pathologically confirmed malignant and benign pathologic lesions of the breast were evaluated with a spectrally selective fat suppression imaging technique to obtain fat-suppressed images of the breast. The technique, a selective partial inversion-recovery (SPIR) method, demonstrated the architectural relationship of malignant and benign tumors with respect to the normal water-containing elements of the breast. These relationships included signs of advanced malignant disease such as tissue retraction, invasive growth, and multicentricity, which appeared on the fat-suppressed images. Fat-suppressed imaging provided useful information for assessing the breasts of both pre- and postmenopausal women, especially in the latter group, where fatty involution of the breast is common. Microcysts, which are normally not visualized by conventional methods, were demonstrated and associated with patients having confirmed fibrocystic disease of the breast. As expected, the SPIR technique did not improve the ability to distinguish between tissues having similar T1 and T2 relaxation time values, such as malignant tumors and normal breast parenchymal tissues. The technique was able to demonstrate that the intense lipid signal, known to be responsible for obscuring the borders of water-fat interfaces and small tumors, could be eliminated in a variety of pathological settings.