通过临床数字红外热成像对疼痛相关热功能障碍进行定量评估。

Quantitative assessment of pain-related thermal dysfunction through clinical digital infrared thermal imaging.

作者信息

Herry Christophe L, Frize Monique

机构信息

Department of Systems and Computer Engineering, Carleton University, 1125 Colonel By Drive, Ottawa, ON K1S 5B6, Canada.

出版信息

Biomed Eng Online. 2004 Jun 28;3(1):19. doi: 10.1186/1475-925X-3-19.

DOI:10.1186/1475-925X-3-19

PMID:15222887

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC455685/

Abstract

BACKGROUND

The skin temperature distribution of a healthy human body exhibits a contralateral symmetry. Some nociceptive and most neuropathic pain pathologies are associated with an alteration of the thermal distribution of the human body. Since the dissipation of heat through the skin occurs for the most part in the form of infrared radiation, infrared thermography is the method of choice to study the physiology of thermoregulation and the thermal dysfunction associated with pain. Assessing thermograms is a complex and subjective task that can be greatly facilitated by computerised techniques.

METHODS

This paper presents techniques for automated computerised assessment of thermal images of pain, in order to facilitate the physician's decision making. First, the thermal images are pre-processed to reduce the noise introduced during the initial acquisition and to extract the irrelevant background. Then, potential regions of interest are identified using fixed dermatomal subdivisions of the body, isothermal analysis and segmentation techniques. Finally, we assess the degree of asymmetry between contralateral regions of interest using statistical computations and distance measures between comparable regions.

RESULTS

The wavelet domain-based Poisson noise removal techniques compared favourably against Wiener and other wavelet-based denoising methods, when qualitative criteria were used. It was shown to improve slightly the subsequent analysis. The automated background removal technique based on thresholding and morphological operations was successful for both noisy and denoised images with a correct removal rate of 85% of the images in the database. The automation of the regions of interest (ROIs) delimitation process was achieved successfully for images with a good contralateral symmetry. Isothermal division complemented well the fixed ROIs division based on dermatomes, giving a more accurate map of potentially abnormal regions. The measure of distance between histograms of comparable ROIs allowed us to increase the sensitivity and specificity rate for the classification of 24 images of pain patients when compared to common statistical comparisons.

CONCLUSIONS

We developed a complete set of automated techniques for the computerised assessment of thermal images to assess pain-related thermal dysfunction.

摘要

背景

健康人体的皮肤温度分布呈现对侧对称性。一些伤害性疼痛和大多数神经性疼痛病症与人体热分布的改变有关。由于通过皮肤散热大部分是以红外辐射的形式发生的，因此红外热成像技术是研究体温调节生理学以及与疼痛相关的热功能障碍的首选方法。评估热像图是一项复杂且主观的任务，计算机技术可极大地促进这项工作。

方法

本文介绍了用于对疼痛热图像进行自动计算机评估的技术，以方便医生做出决策。首先，对热图像进行预处理，以减少初始采集过程中引入的噪声并提取无关背景。然后，使用身体的固定皮节细分、等温分析和分割技术来识别潜在的感兴趣区域。最后，我们使用统计计算和可比区域之间的距离度量来评估感兴趣的对侧区域之间的不对称程度。

结果

当使用定性标准时，基于小波域的泊松噪声去除技术与维纳滤波和其他基于小波的去噪方法相比表现良好。结果表明它对后续分析略有改进。基于阈值化和形态学操作的自动背景去除技术对于有噪声和去噪后的图像均成功，数据库中图像的正确去除率为85%。对于具有良好对侧对称性的图像，成功实现了感兴趣区域（ROI）划定过程的自动化。等温划分很好地补充了基于皮节的固定ROI划分，给出了更准确的潜在异常区域图。与常见的统计比较相比，可比ROI直方图之间的距离度量使我们能够提高对24例疼痛患者图像分类的灵敏度和特异性率。