NEAR-INFRARED,BROAD-BAND SPECTRAL IMAGING OF THE HUMAN BREAST FOR QUANTITATIVE OXIMETRY:APPLICATIONS TO HEALTHY AND CANCEROUS BREASTS

We have examined ten human subjects with a previously developed instrument for near-infrared diffuse spectral imaging of the female breast.The instrument is based on a tandem,planar scan of two collinear optical fibers(one for illumination and one for collection)to image a gently compressed breast in a transmission geometry.The optical data collection features a spatial sampling of 25 points/cm2 over the whole breast,and a spectral sampling of 2 points/nm in the 650-900nm wavelength range.Of the ten human subjects examined,eight are healthy subjects and two are cancer patients with unilateral invasive ductal carcinoma and ductal carcinoma in situ,respectively.For each subject,we generate second-derivative images that identify a network of highly absorbing structures in the breast that we assign to blood vessels.A previously developed paired-wavelength spectral method assigns oxygenation values to the absorbing structures displayed in the second-derivative images.The resulting oxygenation images feature average values over the whole breast that are significantly lower in cancerous breasts(69±14%,n=2)than in healthy breasts(85±7%,n=18)(p<0.01).Furthermore,in the two patients with breast cancer,the average oxygenation values in the cancerous regions are also significantly lower than in the remainder of the breast(invasive ductal carcinoma:49±11%vs 61±16%,p<0.01;ductal carcinoma in situ:58±8%vs 77±11%,p<0.001).

Epileptic brain network mechanisms and neuroimaging techniques for the brain network

Epilepsy can be defined as a dysfunction of the brain network,and each type of epilepsy involves different brain-network changes that are implicated diffe rently in the control and propagation of interictal or ictal discharges.Gaining more detailed information on brain network alterations can help us to further understand the mechanisms of epilepsy and pave the way for brain network-based precise therapeutic approaches in clinical practice.An increasing number of advanced neuroimaging techniques and electrophysiological techniques such as diffusion tensor imaging-based fiber tra ctography,diffusion kurtosis imaging-based fiber tractography,fiber ball imagingbased tra ctography,electroencephalography,functional magnetic resonance imaging,magnetoencephalography,positron emission tomography,molecular imaging,and functional ultrasound imaging have been extensively used to delineate epileptic networks.In this review,we summarize the relevant neuroimaging and neuroelectrophysiological techniques for assessing structural and functional brain networks in patients with epilepsy,and extensively analyze the imaging mechanisms,advantages,limitations,and clinical application ranges of each technique.A greater focus on emerging advanced technologies,new data analysis software,a combination of multiple techniques,and the construction of personalized virtual epilepsy models can provide a theoretical basis to better understand the brain network mechanisms of epilepsy and make surgical decisions.

DiriNet:An Estimation Network for Spectral Response Function and Point Spread Function

Hyper-and multi-spectral image fusion is an important technology to produce hyper-spectral and hyper-resolution images,which always depends on the spectral response function andthe point spread function.However,few works have been payed on the estimation of the two degra-dation functions.To learn the two functions from image pairs to be fused,we propose a Dirichletnetwork,where both functions are properly constrained.Specifically,the spatial response function isconstrained with positivity,while the Dirichlet distribution along with a total variation is imposedon the point spread function.To the best of our knowledge,the neural network and the Dirichlet regularization are exclusively investigated,for the first time,to estimate the degradation functions.Both image degradation and fusion experiments demonstrate the effectiveness and superiority of theproposed Dirichlet network.

Research on the detection of early caries based on hyperspectral imaging

Objective:We applied hyperspectral imaging(HSI)system to distinguish early caries from soundand pigmented areas.It will provide a theoretical basis and technical support,for research anddevelopment of an instrument that could be used for screening and detection of early dentalcaries.Methods:Eighteen extracted human teeth(molars and premolars),with varying degrees ofnatural pathology and no degree of decay involving dentin were obtained.HSI system with awavelength range from 400 to 1000nm was used to obtain images of all 18 teeth containingsound,carious and pigmented areas.We compared the spectra of the wavebands at both 500 nmand 780 nm from the different tooth states,and the reflectance diference bet ween sound versuscarious lesions and sound versus pigmented areas,respectively.Results:There was a slight diference in refectance bet ween carious areas and pigmented areas at500 nm.A substantial difference was additionally noted in refectance bet ween carious areas andpigmented areas at 780 nm.Conclusion:The results have shown that the interference of tooth surface pigment can be elim-inated in the near-infrared(NIR)waveband,and the caries can be effectively identifed from the pigmented areas.Thus,it could be used to detect carious areas of teeth in place of the traditionalvisual inspection method or white light endoscopy.Clinical significance:The NIR difused light signal enables the identification of early caries frompigment and other interference,providing a reasonable detection tool for early detection andearly treatment of teeth diseases.

Functional Imaging of Breast Tissue and Clinical Application

A novel approach to image hemoglobin concentration（△Dhb） and oxygen saturation （△Doxy） of breast tissue is presented. The scenograph of dual-wavelength （760 and 850 nm） near infrared lights through breast tissue is acquired by high sensitive charge coupled device （CCD） camera. The evaluation criterion of the difference of △Dhh and △Doxy between detected and referenced breast tissue can be obtained by a calculation formula without complicate caculation. This approach is applied to clinic detection in breast tissue. The ongoing clinical experiments indicate that malignant tumor usually exhibits characterize of ＂higher △Dhb and lower △Doxy＂, while benign lesion often shows ＂lower △Dhb and higher △Doxy＂ or other characters. So it is useful to assist the diagnosis of breast disease.

DISCRIMINATION OF MENTAL WORKLOAD LEVELS IN HUMAN SUBJECTS WITH FUNCTIONAL NEAR-INFRARED SPECTROSCOPY

We have applied functional near-infrared spectroscopy(fNIRS)to the human forehead to distinguish different levels of mental workload on the basis of hemodynamic changes occurring in the prefrontal cortex.We report data on 3 subjects from a protocol involving 3 mental workload levels based on to working memory tasks.To quantify the potential of fNIRS for mental workload discrimination,we have applied a 3-nearest neighbor classification algorithm based on the amplitude of oxyhemoglobin(HbO2)and deoxyhemoglobin(HbR)concentration changes associated with the working memory tasks.We have found classification success rates in the range of 44%-72%,which are significantly higher than the corresponding chance level(for random data)of 19.1%.This work shows the potential of fNIRS for mental workload classification,especially when more parameters(rather than just the amplitude of concentration changes used here)and more sophisticated classification algorithms(rather than the simple 3-nearest neighbor algorithm used here)are considered and optimized for this application.

Application of the Dempster-Shafer Theory to the Classification of Pixels from Aster Satellite Images and Spectral Indices

In this paper, it is proposed to apply the Dempster-Shafer Theory (DST) or the theory of evidence to map vegetation, aquatic and mineral surfaces with a view to detecting potential areas of observation of outcrops of geological formations (rocks, breastplates, regolith, etc.). The proposed approach consists in aggregating information by using the DST. From pretreated Aster satellite images (geo-referencing, geometric correction and resampling at 15 m), new channels were produced by determining the spectral indices NDVI, MNDWI and NDBaI. Then, the DST formalism was modeled and generated under the MATLAB software, an image segmented into six classes including three absolute classes (E,V,M) and three classes of confusion ({E,V}, {M,V}, {E,M}). The control on the land, based on geographic coordinates of pixels of different classes on said image, has made it possible to make a concordant interpretation thereof. Our contribution lies in taking into account imperfections (inaccuracies and uncertainties) related to source information by using mass functions based on a simple support model (two focal elements: the discernment framework and the potential set of belonging of the pixel to be classified) with a normal law for the good management of these.

Optical neuroimaging:advancing transcranial magnetic stimulation treatments of psychiatric disorders

Transcranial magnetic stimulation(TMS)has been established as an important and effective treatment for various psychiatric disorders.However,its effectiveness has likely been limited due to the dearth of neuronavigational tools for targeting purposes,unclear ideal stimulation parameters,and a lack of knowledge regarding the physiological response of the brain to TMS in each psychiatric condition.Modern optical imaging modalities,such as functional near-infrared spectroscopy and diffuse optical tomography,are promising tools for the study of TMS optimization and functional targeting in psychiatric disorders.They possess a unique combination of high spatial and temporal resolutions,portability,real-time capability,and relatively low costs.In this mini-review,we discuss the advent of optical imaging techniques and their innovative use in several psychiatric conditions including depression,panic disorder,phobias,and eating disorders.With further investment and research in the development of these optical imaging approaches,their potential will be paramount for the advancement of TMS treatment protocols in psychiatry.

基于多位移光谱遥感图像的空间引力模型亚像元定位

目前基于多位移光谱遥感图像的亚像元定位方法通常很少考虑点扩散函数效应影响,本文提出了一种基于多位移光谱遥感图像的空间引力模型亚像元定位方法。为了生成粗糙丰度图像,首先对多个多位移光谱遥感图像进行解混;在点扩散函数效应被考虑的前提下,对粗糙丰度图像实施面积到点的克里插值处理,然后通过理想方波滤波进行滤波,最终获得改进后的粗糙丰度图像;利用空间引力模型对改进后的粗糙丰度图像进行上采样,从而得到上采样丰度图像,再对上采样丰度图像执行整合处理,以生成精细丰度图像;在完成上述所有图像处理步骤后,最终通过应用类别分配方法,将类别标签分发给各个亚像元,以此获得精确的定位结果。在2组实验数据集上的实验结果表明:本文提出的方法比现有的亚像元定位方法获得了更好的定位效果。

光谱CT碘定量评估肾肿瘤患者分肾功能

目的:探究利用光谱计算机体层成像(computed tomography,CT)碘定量评估肾肿瘤患者分肾功能的潜在临床应用价值。方法:回顾并分析50例2周内先后行光谱CT肾脏多期增强及核素肾动态显像的肾肿瘤患者。光谱CT肾脏多期增强扫描采用标准的腹部3期增强方案。手动勾画光谱CT参数肾脏体积(volume,V)、平均CT值(Hounsfield unit,HU)、平均碘浓度值(iodine concentration,IC),并将平均IC与肾脏体积相乘得到碘对比剂累积量K值,同时使用简化的Patlak方程计算得到分肾CT清除率。根据99m锝-二亚乙基三胺五乙酸(^(99m)Tc-diethylene triaminepentaacetic acid,^(99m)Tc-DTPA)肾动态显像盖茨法肾小球滤过率(Gates glomerular filtration rate,Gates GFR)参考值,将100个肾脏分为分肾功能正常组(Gates GFR≥40 mL/min)、分肾功能受损组(Gates GFR<40 mL/min)两组。采用Kruskal-Wallis H检验比较两组间光谱CT各参数的差异,并将各参数与肾动态显像所得Gates GFR进行Spearman相关性分析。绘制受试者工作特征(receiver operating characteristic,ROC)曲线得出分肾CT清除率区分分肾功能正常和分肾功能受损的最佳诊断阈值。结果:光谱CT所得肾脏体积V、动脉期平均CT值HU(t1)、静脉期平均CT值HU(t2)、动脉期平均碘浓度值IC(t1)、静脉期平均碘浓度值IC(t2)、动脉期肾脏碘对比剂累积量K(t1)、静脉肾脏期碘对比剂累积量K(t2)及分肾CT清除率两组之间的差异均有统计学意义(Z/t=-4.459、2.815、-3.313、2.611、-3.609、-4.395、-5.637、-5.815,均P<0.05);并且上述各参数均与GFR相关(r=0.489、0.339、0.481、0.361、0.531、0.590、0.724、0.740,均P<0.001)。区分分肾功能正常与受损的碘定量分肾CT清除率界值为543 mg。结论:光谱CT各参数均可反映分肾功能,其中光谱CT碘定量分肾CT清除率与Gates GFR相关性最高并能区分肾功能是否受损,具有潜在的临床应用价值。

考虑点扩散函数效应的光谱遥感图像超分辨率制图

由于硬件设备的限制和土地覆盖类别的多样性,采集得到的光谱遥感图像的空间分辨率有时较为粗糙,导致大量混合像元产生,严重影响了土地覆盖类型空间分布的制图精度。超分辨率制图技术可以有效地处理光谱遥感图像中的混合像元,获得准确的地物类别分布信息。在遥感大数据背景下,来自同一卫星采集同一区域的多位移图像可以作为辅助数据改进超分辨率制图结果。然而,目前多位移图像插值超分辨率制图方法很少有效地考虑点扩散函数效应影响,导致制图结果精度降低。为了解决这一问题,本文提出了一种考虑点扩散函数效应的多位移光谱遥感图像超分辨率制图方法,改善土地覆盖类别制图结果。在所提出的方法中,首先,对多位移图像进行光谱解混,以生成粗糙丰度图像。然后,在考虑点扩散函数效应的情况下,对粗糙丰度图像先采用面到点克里格法,然后进行理想方波滤波,得到改善的粗糙丰度图像。接下来,通过插值对改善的粗糙丰度图像进行上采样以获得上采样丰度图像,并对上采样的所有丰度图像进行整合以获得精细丰度图像。最后,根据精细丰度图像提供的类别比例信息,使用类别分配方法将类别标签分配给亚像元,以获得理想的制图结果。实验结果表明,通过减少点扩散函数效应影响,所提出的方法展示出最佳性能表现,例如在美国华盛顿特区数据集实验结果的总体精度分别达到77.63%和Kappa系数达到0.7263。

联合SSFs选择与图像去马赛克

图像去马赛克(Demosaicking)是指将马赛克图像重建为RGB彩色图像的过程,其中马赛克图像的每个像素值只包含一个颜色通道,由单个颜色滤波阵列(Color filter array, CFA)来记录,而去马赛克的过程实际上是对马赛克图像每个像素缺失的两个颜色通道进行估值。目前,研究者们虽然已经证实光谱敏感函数(Spectral sensitivity functions, SSFs)对去马赛克有影响,但是现有的SSFs研究大多只专注于通过深度学习进行联合SSFs设计和去马赛克的相关工作,不能保证所设计的SSFs的物理可制造性。基于此,提出联合SSFs选择与图像去马赛克的深度卷积神经网络,通过使用α-Softmax函数设计卷积层针对图像去马赛克任务对已有的SSFs进行选择,选择出对于去马赛克效果最优的SSFs。研究结果表明:使用α-Softmax函数方法能够通过训练一次选择唯一且最优的SSFs,联合方法对去马赛克效果有促进作用。因此,在设计CFA时可以通过使用α-Softmax函数首先选择出最优SSFs,以增强重建图像质量、降低制作成本。

基于SA-CycleGAN的3T磁共振图像生成方法

磁共振成像(Magnetic Resonance Imaging,MRI)广泛应用于临床诊断,相较于1.5T MRI,3T MRI具有高对比度和高信噪比等优势。文章提出了一种基于生成对抗网络融合自注意力机制(SA-CycleGAN)的超场强磁共振图像生成方法,利用生成对抗网络从1.5T MRI生成3T MRI,并将自注意力机制嵌入生成对抗网络框架,引入谱归一化处理,在减少函数振荡的同时加速模型收敛;为提高生成图像的真实性,将先验信息引入网络,提出组合损失函数。使用50对3D磁共振图像训练网络,并用10对图像进行测试。实验结果表明:所提SA-CycleGAN方法生成的磁共振图像的峰值信噪比(PSNR)和结构相似性(SSIM)高于SRGAN、CycleGAN等对比方法。

基于光谱特性的植保机智能图像识别研究

杂草图像识别是植保机作业过程中的关键环节,而利用光谱特性分析技术可以快速对种植区域的杂草进行识别。为此,利用ASD光谱分析仪连续进行5组光谱数据采集,经分析处理后得出光谱数据;按照最小值原则选取595、710、755、950nm共4个特征波长,建立典型判别函数模型和贝叶斯判别函数模型,对预测集合数据进行预测。结果表明:贝叶斯判别函数模型能够较好地进行种植区域杂草图像识别,且模型具有较高的稳定性,为植保机杂草图像识别探测传感器的开发提供了参考依据。

结合光谱角的最大似然法遥感影像分类

遥感影像含有丰富的信息,反映了地物特征。其中光谱角侧重描述了光谱的形状特征,具有对多光谱图像增益不敏感的特点。最大似然法是遥感影像分类最常用的方法之一,文中对该方法的后验概率判别函数进行修改,将光谱角以概率因子的形式加入到判别函数中构造一种新的判别函数,有机地将光谱角这一特征信息加入影像分类。通过实验,并与最大似然法和光谱角匹配法分类结果进行比较,结果表明,结合光谱角的最大似然分类法的分类精度得到提高。

一种新的全色与多光谱图像融合变分模型

图像融合是提供包含各输入图像互补信息的单幅图像的有力工具.本文提出了一种新的用于全色和多光谱图像融合的变分模型.在Socolinsky对比度模型的基础上构造了一个改进的能量泛函最小化问题,以寻找最接近全色图像梯度的解.为了提高多光谱图像的空间分辨率,并尽可能地保持其原有的光谱信息,还将光谱一致项、波段间相关项和对比度增强项引入融合模型.在IKONOS和QuickBird数据集上测试了该模型的性能.实验结果表明该模型可以生成同时具有高空间质量和高光谱质量的融合图像.

基于压缩感知的稀疏无源雷达成像

当窄带外辐射源数目稀少且空间分布不均匀时,通常会在无源雷达成像中产生稀疏的无规则空间谱填充,使得传统快速逆傅里叶方法(inverse fast Fourier transform,IFFT)或极坐标方法难以获得良好的目标成像效果。针对这种空间谱填充的稀疏性和非均匀性,利用压缩感知理论在处理稀疏随机采样信号重构问题上的优势,提出了稀疏无源雷达成像方法。同时通过构造传感矩阵的互相关和积累相关函数,对目标图像的可重构性进行了分析。理论分析和仿真结果表明,对具有稀疏随机空间谱特点的无源雷达成像,本文提出的成像方法是有效的。

C^s相似度函数下正则谱聚类的收敛阶(英)

用覆盖数逼近的方法给出Cs相似度函数下正则谱聚类的收敛阶.

基于光谱响应函数的遥感图像融合对比研究

遥感图像融合是一个十分重要的问题,目前已出现了很多融合方法。一些现有方法可以从高空间分辨率全色数据中提取细节特征,并注入到低空间分辨率多光谱数据中,同时尽可能保持多光谱数据的光谱特性。现有方法一般都不能利用遥感成像系统的物理信息,因此可能导致融合结果发生严重的光谱扭曲。该文采用适当的遥感图像融合模型对图像融合问题进行分解,将融合问题归结为空间细节调制参数构建与空间细节信息提取两个子问题,在对传感器光谱响应函数(SRF)的分析基础上,构建合理的空间细节调制参数。依据对现有方法的分类,文章将三种基于SRF的空间细节调制参数构建方法,与高斯高通滤波提取的空间细节信息结合,产生三种基于SRF的遥感图像融合方法。这些方法在Ikonos数据上进行了试验和分析,并与GS和HPM方法进行了对比。

高速窄带多光谱成像系统光谱重建技术研究

光谱成像技术可以同时从光谱维和空间维上获取被测目标的信息,即结合了空间成像系统和光谱检测系统的功能,因此近年在影像获取与处理领域中倍受重视。本论文基于窄带多光谱成像技术建立八通道CCD多光谱成像系统,它能够实时采集八个通道的图像,获得波长分布从可见到红外(420—940nm)八个波段的光谱响应值。在此基础上对图像进行位置配准、反射率定标、采用插值算法获得其它波段光谱响应值,最终能够获取图像中任意一点的光谱反射率及颜色参数。实验结果表明,本文使用的三次样条插值法对原始光谱图像进行平滑操作的方法是有效的,能够以一定精度模拟出目标物点的真实光谱特性。该系统在动态目标检测识别、艺术品评价复制等领域有着广阔的应用前景。