高光谱成像技术在生物医学中的应用

高光谱成像技术是传统成像与光谱技术相结合的一门新技术,其可同时获得被测物体的空间特征与光谱信息,以实现对物质特性的研究。本文介绍了高光谱成像技术的基本原理、系统的基本构成及特点,总结和阐述了近年来高光谱成像技术在生物医学领域的发展,以及其在疾病诊断中的应用。     

磁共振水成像对脊柱疾病诊断中的应用价值

目的：探讨磁共振水成像技术对脊柱疾病诊断的应用价值.方法：采用快速高级自旋回波（FASE）、重T2WI及脂肪抑制序列对300例病人检查行磁共振椎管水成像（MR myelography,MRM）.结果：MRM显示正常25例,MRM异常275例,清楚显示原发病变与邻近脊髓腔、脊髓、神经根的相关关系.结论：MRM具有无创伤、无辐射、速度快,不需对比剂,患者易接受的特点.MRM与常规MRI图像结合可获得全面、客观的病变信息,MRM图像可取代X线脊髓造影和CT脊髓造影.     

人手部皮下微循环特性随深度变化的研究

本研究使用手持式扫频光学相干层析(SSOCT)系统分别在人左手无名指指甲上方、无名指指腹和手掌大拇指根部选取3 mm×3 mm区域进行了在体成像,使用指数补偿方法还原血流信息,获取不同深度的血流正面光学断层图像(en face图像),从血管灌注密度(PD)、血管直径(VD)两个方面分析了微循环随深度的变化特性。试验结果证明,在上述三个成像位置中,随着成像深度的增加,血管PD与血管VD均增大,血流信息的丰富程度增加,但同时en face图像的清晰度有所下降。其中左掌大拇指根部微血管最为细密,血流信息较为丰富,比较适宜作为微循环疾病诊断研究的成像部位。分层投影结果显示,左手无名指指甲上方部位在成像深度较浅(220～660μm)时,血管PD明显小于其他两个成像部位,说明此处在该范围内血流信息丰富程度不够。本文测量了随深度变化的手部血流几何学特征,验证了光学相干层析(OCT)技术基于手部皮下微循环光学断层图像进行疾病诊断的可行性。许多微循环疾病早期就已经产生了微血管病变,因此对这种微循环变化的探测在疾病的早期诊断方面具有临床指导意义。     

磁共振成像设备发展趋势

本文主要叙述了磁共振设备的原理、构造、产品发展趋势。并对提高磁共振图像分辨的新技术,如Tim全景矩阵成像、自由浪潮技术、高清晰MRI技术和双梯度技术作了综述。     

用于动物分类学研究领域的显微成像新技术

UV-C光学共聚焦显微图像系统集成了光学和数字图像分析技术，特别适用于采集非平面样品（高度变化范围超过了显微镜景深范围）的图像，它彻底解决了传统光学显微镜成像时高倍数与大景深不能共存的问题，使样品的不同高低部位都能清晰成像，可以获得像电镜图像一样的巨大景深和精致的细节，     

正常人群磁共振全身弥散加权成像特点的初步研究

目的：探讨健康志愿者不同性别各年龄组人体多脏器全身弥散加权成像的图像特征。方法：对50例健康志愿者行全身弥散加权成像扫描,其中,20．30岁、30．40岁、40—50、50．60、60岁以上各二十例,每组内男女各十例。所得图像均经nDeMR后处理工作站（AW4．3）行MIP重建和黑白反转显示技术,并重建ADC图,观察不同性别各年龄组人体多脏器弥散加权图像的特点,并测定不同部位的ADC值,测量的部位主要包括脑灰质、脑白质、尾状核头、丘脑、桥脑、腮腺、肝脏、脾脏、T8椎体、T8—9椎间盘、L2椎体、L2．3椎间盘、前列腺、乳腺、子宫颈等,每个部位重复测量三次取平均值,单位为×10^-3mm^2／S。结果：1、WB-DWI的正常表现。2、不同性别及年龄组间各组织器官ADC值的统计学分析脑白质、T8椎体ADC值在不同性别及年龄组之间存在统计学差异（P〈0．05）;T8．9椎间盘、L2．3椎间盘及女性乳腺ADC值在不同年龄组之间存在统计学差异（P〈0．05）;L2椎体ADC值在男女之间存在统计学差异（P〈0．05）。3、不同部位ADC值平均值。结论：正常人体不同组织器官弥散加权图像特点及ADC值受到性别、年龄的影响,不同性别各年龄组的正常WB-DWI表现存在差异。了解健康成人正常WB-DWI的表现对于准确判断各组织器官的疾病有着重要的意义。     

用于动物分类学研究领域的显微成像新技术

UV-C光学共聚焦昱微图像系统集成了光学和数字图象分析技术,特别适用于采集非平面样品（高度变化范围超过了显微镜景深范围）的图象,它彻底解决了传统光学显微镜成像时高倍数与大景深不能共存的问题,使样品的不同高低部位都能清晰成像,可以获得像电镜图像一样的巨大景深和精致的细节,     

用于动物分类学研究领域的显微成像新技术

UV—C光学共聚焦显微图像系统集成了光学和数字图像分析技术，特别适用于采集非平面样品（高度变化范围超过了显微镜景深范围）的图像，它彻底解决了传统光学显微镜成像时高倍数与大景深不能共存的问题，使样品的不同高低部位都能清晰成像，可以获得像电镜图像一样的巨大景深和精致的细节，更能得到电镜图像所没有的真实色彩。UV—C以清晰直观的样品图片带给读者手绘图所不能达到的视觉效果，是动物分类学家研究和描述物种的好助手。     

用于动物分类学研究领域的显微成像新技术

UV—C光学共聚焦显微图像系统集成了光学和数字图像分析技术，特别适用于采集非平面样品（高度变化范围超过了显微镜景深范围）的图像，它彻底解决了传统光学显微镜成像时高倍数与大景深不能共存的问题，使样品的不同高低部位都能清晰成像，可以获得像电镜图像一样的巨大景深和精致的细节，更能得到电镜图像所没有的真实色彩。UV—C以清晰直观的样品图片带给读者手绘图所不能达到的视觉效果，是动物分类学家研究和描述物种的好助手。     

利用散射光声微分成像技术实现弱吸收物质显微成像

光声显微成像技术依赖于样品的内源性光吸收,对强散射弱吸收样品成像效果差,甚至无法进行成像。为了实现强散射弱吸收高透明生物样品的光声显微成像,以及获得图像的边缘增强效果,使光声显微成像技术在实际的生物医学研究中更有应用价值,本文首次将散射光声技术引入到光声微分显微技术中,研制了新型的散射光声微分成像技术。该技术不仅可以获得强散射弱吸收高透明生物样品的散射光声显微图像,还可以获得对应的边缘清晰的散射光声微分图像,对在生物医学研究领域有重要的应用意义。     

Hyperspectral imaging of mucosal surfaces in patients

The aim of this study was to proof applicability of hyperspectral imaging for the analysis and classification of human mucosal surfaces in vivo. The larynx as a prototypical anatomically well‐defined surgical test area was analyzed by microlaryngoscopy with a polychromatic lightsource and a synchronous triggered monochromatic CCD‐camera. Image stacks (5 benign, 7 malignant tumors) were analyzed by established software (principal component analysis PCA, hyperspectral classification, spectral profiles). Hyperspectral image datacubes were analyzed and classified by conventional software. In PCA, images at 590–680 nm loaded most onto the first PC which typically contained 95% of the total information. Hyperspectral classification clustered the data highlighting altered mucosa. The spectral profiles clearly differed between the different groups. Hyperspectral imaging can be applied to mucosal surfaces. This approach opens the way to analyze spectral characteristics of histologically different lesions in order to build up a spectral library and to allow non‐touch optical biopsy. (© 2012 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Microscopic hyperspectral imaging studies of normal and diabetic retina of rats

A microscopic hyperspectral imager was developed based on the microscopic technology and the spectral imaging technology. Some microscopic hyperspectral images of retina sections of the normal, the diabetic, and the treated rats were collected by the new imager. Single-band images and pseudo-color images of each group were obtained and the typical transmittance spectrums were ex-tracted. The results showed that the transmittance of outer nuclear layer cells of the diabetic group was generally higher than that of the normal. A small absorption peak appeared near the 180th band in the spectrum of the diabetic group and this peak weakened or disappeared in the spectrum of the treated group. Our findings indicate that the microscopic hyperspectral images include wealthy information of retina sections which is helpful for the ophthalmologist to reveal the pathogenesis of diabetic reti-nopathy and explore the therapeutic effect of drugs.     

微波热声成像技术用于人体甲状腺检测

本文首次通过人体实验验证了微波热声成像技术用于人体甲状腺检测的可行性.文章首先讨论了该技术用于人体甲状腺检测的可行性;然后对3名志愿者的健康甲状腺进行了微波热声成像实验.结果表明:微波热声成像能够对人体健康甲状腺进行清晰成像,能够真实反映皮肤、甲状腺和气管等不同组织的结构特征;并且一次完整的检测过程时间约5 s,系统操作简单成像快速.综上所述,微波热声成像技术有望为甲状腺疾病的基础研究和临床诊断提供一种新的影像学参考.     

Hyperspectral imaging: a novel approach for microscopic analysis

BACKGROUND: The usefulness of the light microscope has been dramatically enhanced by recent developments in hardware and software. However, current technologies lack the ability to capture and analyze a high-resolution image representing a broad diversity of spectral signatures in a single-pass view. We show that hyperspectral imaging offers such a technology. METHODS AND RESULTS We developed a prototype hyperspectral imaging microscope capable of collecting the complete emission spectrum from a microscope slide. A standard epifluorescence microscope was optically coupled to an imaging spectrograph, with output recorded by a CCD camera. Software was developed for image acquisition and computer display of resultant X--Y images with spectral information. Individual images were captured representing Y-wavelength planes, with the stage successively moved in the X direction, allowing an image cube to be constructed from the compilation of generated scan files. This prototype instrument was tested with samples relevant to cytogenetic, histologic, cell fusion, microarray scanning, and materials science applications. CONCLUSIONS: Hyperspectral imaging microscopy permits the capture and identification of different spectral signatures present in an optical field during a single-pass evaluation, including molecules with overlapping but distinct emission spectra. This instrument can reduce dependence on custom optical filters and, in future imaging applications, should facilitate the use of new fluorophores or the simultaneous use of similar fluorophores.     

Alien Plant Monitoring with Ultralight Airborne Imaging Spectroscopy

Effective management of invasive plants requires a precise determination of their distribution. Remote sensing techniques constitute a promising alternative to field surveys and hyperspectral sensors (also known as imaging spectrometers, with a large number of spectral bands and high spectral resolution) are especially suitable when very similar categories are to be distinguished (e.g. plant species). A main priority in the development of this technology is to lower its cost and simplify its use, so that its demonstrated aptitude for many environmental applications can be truly realized. With this aim, we have developed a system for hyperspectral imaging (200 spectral bands in the 380–1000 nm range and circa 3 nm spectral resolution) operated on board ultralight aircraft (namely a gyrocopter), which allows a drastic reduction of the running costs and operational complexity of image acquisition, and also increases the spatial resolution of the images (circa 5–8 pixels/m² at circa 65 km/h and 300 m height). The detection system proved useful for the species tested (Acacia melanoxylon, Oxalis pes-caprae, and Carpobrotus aff. edulis and acinaciformis), with user’s and producer’s accuracy always exceeding 90%. The detection accuracy reported corresponds to patches down to 0.125 m² (50% of pixels 0.5×0.5 m in size), a very small size for many plant species, making it very effective for initial stages of invasive plant spread. In addition, its low operating costs, similar to those of a 4WD ground vehicle, facilitate frequent image acquisition. Acquired images constitute a permanent record of the status of the study area, with great amount of information that can be analyzed in the future for other purposes, thus greatly facilitating the monitoring of natural areas at detailed spatial and temporal scales for improved management.     

Growth characteristics of three Fusarium species evaluated by near-infrared hyperspectral imaging and multivariate image analysis

Colony growth of three Fusarium spp. on potato dextrose agar was followed by collecting near-infrared (NIR) hyperspectral images of the colonies at regular intervals after inoculation up to 55?h. After principal component analysis (PCA), two clusters were apparent in the score plot along principal component 1. Using the brushing technique, these clusters were divided into four groups of pixels with similar score values. These could be visualised as growth zones within the colonies in the corresponding score image. Three spectral bands, i.e. 1,166, 1,380 and 1,918?nm, were prominent in the multiplicative scatter corrected and Savitzky?CGolay second derivative spectra. These indicated chemical changes, associated with carbohydrates (1,166 and 1,380?nm) and protein (1,918?nm), that occurred as the mycelium grew and matured. The protein band was more prominent in the mature fungal material while the carbohydrate band was less pronounced. The younger material and the agar were characterised by the carbohydrate spectral band. Integrating whole mycelium colonies as the sum of pixels over time made it possible to construct curves that resembled growth curves; this included the lag phase, active growth phase, deceleration phase and phase of constant growth. Growth profiles constructed from individual growth zones indicated more detailed growth characteristics. The use of NIR hyperspectral imaging and multivariate image analysis (MIA) allowed one to visualise radial growth rings in the PCA score images. This would not have been possible with bulk spectroscopy. Interpreting spectral data enabled better understanding of microbial growth characteristics on agar medium. NIR hyperspectral imaging combined with MIA is a powerful tool for the evaluation of growth characteristics of fungi.     

Detection and Discrimination of Tea Plant Stresses Based on Hyperspectral Imaging Technique at a Canopy Level

Tea plant stresses threaten the quality of tea seriously. The technology corresponding to the fast detection and differentiation of stresses is of great significance for plant protection in tea plantation. In recent years, hyperspectral imaging technology has shown great potential in detecting and differentiating plant diseases, pests and some other stresses at the leaf level. However, the lack of studies at canopy level hampers the detection of tea plant stresses at a larger scale. In this study, based on the canopy-level hyperspectral imaging data, the methods for identifying and differentiating the three commonly occurred tea stresses (i.e., the tea leafhopper, anthrax and sun burn) were studied. To account for the complexity of the canopy scenario, a stepwise detecting strategy was proposed that includes the process of background removal, identification of damaged areas and discrimination of stresses. Firstly, combining the successive projection algorithm (SPA) spectral analysis and K-means cluster analysis, the background and overexposed non-plant regions were removed from the image. Then, a rigorous sensitivity analysis and optimization were performed on various forms of spectral features, which yielded optimal features for detecting damaged areas (i.e., YSV, Area, GI, CARI and NBNDVI) and optimal features for stresses discrimination (i.e., MCARI, CI, LCI, RARS, TCI and VOG). Based on this information, the models for identifying damaged areas and those models for discriminating different stresses were established using K-nearest neighbor (KNN), Random Forest (RF) and Fisher discriminant analysis. The identification model achieved an accuracy over 95%, and the discrimination model achieved an accuracy over 93% for all stresses. The results suggested the feasibility of stress detection and differentiation using canopy-level hyperspectral imaging techniques, and indicated the potential for its extension over large areas.     

基于光谱特征变量的湿地典型植物生态类型识别方法——以北京野鸭湖湿地为例

光谱特征变量的选择对于湿地植被识别的精度和效率有着直接的影响作用.以华北地区典型的淡水湿地——野鸭湖湿地为研究区,采用Field Spec 3野外高光谱辐射仪,获取了野鸭湖典型湿地植物的冠层光谱.以野外高光谱数据为基础,首先利用一阶导数与包络线去除的方法,分析和对比不同植物生态类型的光谱特征,选定了用于识别植物生态类型的光谱特征变量,选定的8个光谱特征变量为红边位置WP_r、红边幅值Dr、绿峰位置WP_g、绿峰幅值Rg、510 nm附近的吸收深度DEP-510和吸收面积AREA-510、675 nm附近的吸收深度DEP-675和吸收面积AREA-675.其中,7种植物生态类型的一阶导数光谱特征差异较小,吸收特征差异性相对较大.除WP_r和WP _g外,沉水植物Rg和Dr平均值最低,湿生植物的Rg平均值最高,达到0.164,栽培植物的Dr平均值最高,达到0.012.7种植物生态类型在675 nm附近的DEP-675和AREA-675均高于510 nm附近的DEP-510与AREA-510,除去栽培植物,随着水分梯度的变化,其他6种植物生态类型的吸收深度和吸收面积都表现出先升高后降低的趋势.然后利用单因素方差分析(One-way ANOVA)验证了所选光谱特征变量的区分度,在P≤0.01的置信水平下,选取的8个光谱特征变量都能够较好的区分7种植物生态类型,区分度的最小值为13,最大值为18,并且吸收特征参数的区分度优于一阶导数参数.最后应用非线性的反向传播人工神经网络(BP-ANN)与线性判别分析(FLDA)的类型识别方法,利用选定的8个光谱特征变量进行湿地植物生态类型识别,取得了较好的识别精度,两种方法的总分类精度分别达到85.5％和87.98％.单因素方差分析(One-way ANOVA)和不同分类器的分类精度表明,所选的8个光谱特征变量具有一定的普适性和可靠性.     

Imaging depth variations in hyperspectral imaging: Development of a method to detect tumor up to the required tumor‐free margin width

Hyperspectral imaging is a promising technique for resection margin assessment during cancer surgery. Thereby, only a specific amount of the tissue below the resection surface, the clinically defined margin width, should be assessed. Since the imaging depth of hyperspectral imaging varies with wavelength and tissue composition, this can have consequences for the clinical use of hyperspectral imaging as margin assessment technique. In this study, a method was developed that allows for hyperspectral analysis of resection margins in breast cancer. This method uses the spectral slope of the diffuse reflectance spectrum at wavelength regions where the imaging depth in tumor and healthy tissue is equal. Thereby, tumor can be discriminated from healthy breast tissue while imaging up to a similar depth as the required tumor‐free margin width of 2 mm. Applying this method to hyperspectral images acquired during surgery would allow for robust margin assessment of resected specimens. In this paper, we focused on breast cancer, but the same approach can be applied to develop a method for other types of cancer.