红外热成像辅助面神经功能自动评估方法研究

面瘫是一种多发的面神经疾病,表现为患侧面神经功能失调,严重影响患者的正常生活和人际交往。面神经功能自动评估方法对于面瘫的诊治是至关重要的。面部神经功能受损导致体表温度分布发生改变,可以通过红外热成像采集患者的面部温度分布不对称特征,基于红外热成像提出一种面神经功能自动评估新方法,融合温度特异性和边缘检测自动将面部红外热像划分为左右对称的八个区域,提取面部温度不对称特征,包括温差、有效热面积比和温度分布不对称度,采用径向基神经网络作为面神经功能自动分类器。实验收录了390幅单侧患病的面瘫患者正面红外热像图,结果显示：采用径向基神经网络的红外热成像面神经功能自动分类器的平均分类准确率为94.10%,比采用K近邻分类器和支持向量机分类器分别提高了9.31%和4.87%,优于传统的House-Brackmann面神经功能评估方法,对面神经功能的分类精度完全符合临床应用标准,可以有效评估面瘫患者的面神经功能,有助于面瘫的临床诊断与治疗。     

基于红外热成像与形式概念分析的面瘫病情客观评估方法

面部神经功能障碍导致面瘫患者患侧面部肌肉运动功能失控,给患者的外貌、生理和情感带来巨大的打击。一种客观量化的面瘫病情严重度评估方法对于面瘫的治疗是至关重要的。提出了一种基于红外热像图和形式概念分析的面瘫严重度评估新方法,共收录了单侧患病的面瘫患者65例。应用红外热成像法,在1月内每隔5天采集一次面瘫患者的面部温度分布图像,将面部红外热像进行预处理,划分为左右对称的六个区域,提取并分析面部左右两侧对称区域的温差,利用形式概念分析挖掘温差与面瘫严重度的关系。结果显示：面瘫患者面部温度分布呈现双侧不对称性,面部区域的双侧温差大于0.2 ℃,而正常人体面部区域的两侧温差均小于0.2 ℃。面部区域的双测温差与面瘫严重度的相关系数平均为0.508。此外,如其中一个区域的左右两侧温差大于0.2 ℃,并且全部小于0.5 ℃,则可以判定面瘫为轻中度;面部任一区域的左右两侧温差大于0.5 ℃,则可以判定面瘫为重度。这种基于形式概念分析的红外热像计算机分析方法可用于评估面瘫导致的面部热失调,有助于面瘫的临床诊断与治理。     

对称与不对称，哪个更根本

一、物理学中的对称及启示对称就是指物体相同部分有规律的重复。对称变换亦称对称操作,是指使对称物体(或图形)中的各个相同部分,作有规律重复的变换动作。德国女数学家艾米.诺特(EmmyNoether,1882~1935)指出:如果运动规律在某一变换下具有不变性,必然存在一个对应的守恒定律。爱因斯坦建立狭义相对论的开创性论文《论动体的电动力学》开头是这样写的:大家知道,麦克斯韦电动力学(像现在通常为人们所理解的那样)在用于运动物体时,就要引起一些不对称,而这种不对称似乎不是现象所固有的。他这里所说的不对称,指的是闭合导体(如螺线管)相对磁…     

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。     

用红外热成像技术测量MEMS器件的热特性

微电子机械系统(MEMS)的很多器件均凭借热工作原理,在其设计、性能评估中都需要了解热特性,特别是温度分布的动静态特性。本文用显微红外热成像技术测试分析了气体传感器微热板、微机械热对流加速度计的微加热器、热驱动微热泵芯片的温度分布特性及微辐射热计的热阻特性。在测试中考虑了对象的有效发射率等影响测量精度的系统因素。     

红外热波无损检测中材料表面下缺陷类型识别的有限元模拟及分析

鉴于红外热波无损检测中被检测物的形状、尺寸、材料和缺陷类型的不同，为给红外热波无损检测提供前期实验结果的预演，利用大型有限元分析软件ANSYS选择3种热特性差异较大的均匀材料，设计了三维模型。利用软件的前处理器和通用后处理器，绘出不同时刻模型表面的温度场分布，以此确定温度分布材料缺陷的类型。通过对模拟数据进行分析，绘出不同缺陷的温度变化曲线。根据曲线斜率的不同，可定性确定缺陷的类型。模拟结果说明：大型有限元分析软件ANSYS可用于红外热波无损检测实验过程的模拟,模拟结果与实验结果相符。该方法可用于其他不同缺陷类型的模拟及定量识别。     

红外热像仪SiTF的测试研究

信号传递函数(SiTF)是评价红外热像仪性能的最基本且最关键的技术指标之一，它是响应度函数的线性部分，从响应度函数测试曲线中可得到待测系统增益、线性度、动态范围和饱和度的信息。采用高精度的双黑体反射靶标评估系统对CEDIT IIA型热像仪的SiTF进行了测试分析。该系统保证了背景辐射的均匀稳定，且受环境温度变化的影响极小，从而大大提高了测量的准确性和可靠性。最后给出了测试SiTF时出现波动的多种可能原因。     

摩擦不对称耦合布朗马达的定向输运

本文研究了耦合布朗马达在溶液摩擦对称性破缺条件下的定向输运问题.详细讨论了溶液阻尼系数比,周期外力以及耦合作用对布朗粒子定向输运的影响.研究发现:溶液摩擦的不对称性不仅能促进摩擦棘轮的定向输运,且合适的溶液阻尼系数比还可以使耦合棘轮的定向输运达到最强.此外,一定摩擦阻尼条件下外力振幅可以使耦合粒子的定向输运呈现多峰结构.研究还发现合适的自由长度和耦合强度也能增强摩擦棘轮的输运特性.研究结果不仅能够启发实验上选取合适的摩擦阻尼来优化布朗马达的输运,也可为信息容量大、反应速度快的纳米器件的制备提供一定的理论参考.     

湿法腐蚀进程的红外热像学研究

提出了一种研究湿法腐蚀进程的新方法———红外热像法。在湿法腐蚀中,金属或半导体基片浸泡在化学试剂中,由于化学能的作用,会在溶剂中产生热能,从而发出红外辐射,利用红外热像仪,将探测到的红外辐射信号送至计算机进行处理,得到热像图,从而可以对湿法腐蚀的进程进行分析。理论分析和实验结果都表明,红外热像法可以直观地观测到湿法腐蚀时显著的热扩散过程,从而对湿法腐蚀进程的监测、控制具有指导意义,同时也是红外技术应用的扩展。     

Validation of hard tooth tissue thermal diffusivity measurements applying an infrared camera

The problem concerns investigations of thermophysical properties of small biological specimens. Results of experimental verification of some thermal diffusivity data of hard tooth tissue are presented and discussed. The measurements have been performed on two sliced tooth specimens of different thicknesses. The temperature changes of one flat surface have been recorded applying an infrared camera while the opposite surface has been monotonously heated. The results of measurements have been analysed in order to identify the differences related to variations in thermal properties of hard tooth tissues. Distinct differences between heated enamel, crown dentine and root dentine structures have been revealed. Lack of analytical heat transfer formulae restricted the analysis to qualitative aspects of the problem. Conclusions concerning possible quantitative calculations and the methodology of such an analysis have been formulated.     

A review on the application of medical infrared thermal imaging in hands

Infrared Thermal (IRT) imaging is a medical imaging modality to study skin temperature in real time, providing physiological information about the underlining structures. One of the most accessible body sites to be investigated using such imaging method is the hands, which can reflect valuable information about conditions affecting the upper limbs. The aim of this review is to acquaint the successful applications of IRT in the hands with a medical scope, opening horizons for future applications based in the achieved results. A systematic literature review was performed in order to assess in which applications medical IRT imaging was applied to the hands. The literature search was conducted in the reference databases: PubMed, Scopus and ISI Web of Science, making use of keywords (hand, thermography, infrared imaging, thermal imaging) combination that were present at the title and abstract. No temporal restriction was made. As a result, 4260 articles were identified, after removal of duplicates, 3224 articles remained and from first title and abstract filtering, a total of 388 articles were considered. After application of exclusion criteria (non-availability, non-clinical applications, reviews, case studies, written in other languages than English and using liquid crystal thermography), 146 articles were considered for this review. It can be verified that thermography provides useful diagnostic and monitoring information of conditions that directly or indirectly related to hands, as well as aiding in the treatment assessment. Trends and future challenges for IRT applications on hands are provided to stimulate researchers and clinicians to explore and address them.     

Suitable features selection for monitoring thermal condition of electrical equipment using infrared thermography

Monitoring the thermal condition of electrical equipment is necessary for maintaining the reliability of electrical system. The degradation of electrical equipment can cause excessive overheating, which can lead to the eventual failure of the equipment. Additionally, failure of equipment requires a lot of maintenance cost, manpower and can also be catastrophic- causing injuries or even deaths. Therefore, the recognition processof equipment conditions as normal and defective is an essential step towards maintaining reliability and stability of the system. The study introduces infrared thermography based condition monitoring of electrical equipment. Manual analysis of thermal image for detecting defects and classifying the status of equipment take a lot of time, efforts and can also lead to incorrect diagnosis results. An intelligent system that can separate the equipment automatically could help to overcome these problems. This paper discusses an intelligent classification system for the conditions of equipment using neural networks. Three sets of features namely first order histogram based statistical, grey level co-occurrence matrix and component based intensity features are extracted by image analysis, which are used as input data for the neural networks. The multilayered perceptron networks are trained using four different training algorithms namely Resilient back propagation, Bayesian Regulazation, Levenberg–Marquardt and Scale conjugate gradient. The experimental results show that the component based intensity features perform better compared to other two sets of features. Finally, after selecting the best features, multilayered perceptron network trained using Levenberg–Marquardt algorithm achieved the best results to classify the conditions of electrical equipment.     

Improving spatio-temporal resolution of infrared images to detect thermal activity of defect at the surface of inorganic glass

This paper proposes a noise suppression methodology to improve the spatio-temporal resolution of infrared images. The methodology is divided in two steps. The first one consists in removing the noise from the temporal signal at each pixel. Three basic temporal filters are considered for this purpose: average filter, cost function minimization (FIT) and short time Fast Fourier Transform approach (STFFT). But while this step effectively reduces the temporal signal noise at each pixel, the infrared images may still appear noisy. This is due to a random distribution of a residual offset value of pixels signal. Hence in the second step, the residual offset is identified by considering thermal images for which no mechanical loading is applied. In this case, the temperature variation field is homogeneous and the value of temperature variation at each pixel is theoretically equal to zero. The method is first tested on synthetic images built from infrared computer-generated images combined with experimental noise. The results demonstrate that this approach permits to keep the spatial resolution of infrared images equal to 1 pixel. The methodology is then applied to characterize thermal activity of a defect at the surface of inorganic glass submitted to cyclic mechanical loading. The three basic temporal filters are quantitatively compared and contrasted. Results obtained demonstrate that, contrarily to a basic spatio-temporal approach, the denoising method proposed is suitable to characterize low thermal activity combined to strong spatial gradients induced by cyclic heterogeneous deformations.     

Wavelet subspace decomposition of thermal infrared images for defect detection in artworks

Health of ancient artworks must be routinely monitored for their adequate preservation. Faults in these artworks may develop over time and must be identified as precisely as possible. The classical acoustic testing techniques, being invasive, risk causing permanent damage during periodic inspections. Infrared thermometry offers a promising solution to map faults in artworks. It involves heating the artwork and recording its thermal response using infrared camera. A novel strategy based on pseudo-random binary excitation principle is used in this work to suppress the risks associated with prolonged heating. The objective of this work is to develop an automatic scheme for detecting faults in the captured images. An efficient scheme based on wavelet based subspace decomposition is developed which favors identification of, the otherwise invisible, weaker faults. Two major problems addressed in this work are the selection of the optimal wavelet basis and the subspace level selection. A novel criterion based on regional mutual information is proposed for the latter. The approach is successfully tested on a laboratory based sample as well as real artworks. A new contrast enhancement metric is developed to demonstrate the quantitative efficiency of the algorithm. The algorithm is successfully deployed for both laboratory based and real artworks.     

Measurement of thermal parameters of a heat insulating material using infrared thermography

The article presents results of research developing methods for determining thermal parameters of a thermal insulating material. This method applies periodic heating as an excitation and an infrared camera is used to measure the temperature distribution on the surface of the tested material. The usefulness of known analytical solution of the inverse problem was examined in simulation study, using a three-dimensional model of the heat diffusion phenomenon in the sample of the material under test. To solve the coefficient inverse problem an approach using an artificial neural network is proposed. The measurements were performed on an experimental setup equipped with a ThermaCAM PM 595 infrared camera and a frame grabber. The experiment allowed verification of the chosen 3-D model of the heat diffusion phenomenon and proved suitability of the proposed test method.     

Low-velocity impact damage characterization of carbon fiber reinforced polymer (CFRP) using infrared thermography

Carbon fiber reinforced polymer (CFRP) after low-velocity impact is detected using infrared thermography, and different damages in the impacted composites are analyzed in the thermal maps.The thermal conductivity under pulse stimulation, frictional heating and thermal conductivity under ultrasonic stimulation of CFRP containing low-velocity impact damage are simulated using numerical simulation method. Then, the specimens successively exposed to the low-velocity impact are respectively detected using the pulse infrared thermography and ultrasonic infrared thermography. Through the numerical simulation and experimental investigation, the results obtained show that the combination of the above two detection methods can greatly improve the capability for detecting and evaluating the impact damage in CFRP. Different damages correspond to different infrared thermal images. The delamination damage, matrix cracking and fiber breakage are characterized as the block-shape hot spot, line-shape hot spot, and “

” shape hot spot respectively.     

Optimizing thermography depth probing with a dynamic thermal point spread function

Derivation of two point spread functions PSFs suitable for infrared thermograms analysis is illustrated, based on two unique approaches, one based on depth decaying limit and one on diffusion limit. Experimental work using PMMA sample with back drilled holes and pulsed thermographic routine is utilized to show the effectiveness of deconvoluting pixel temperature transient history with suggested PSF’s. Synthetic second time derivative thermograms are utilized for comparison and the signal to noise ratio is used as a figure of merit for quantification.