Xuan Jianhua, Klimach Uwe, Zhao Hongzhi, Chen Qiushui, Zou Yingyin, Wang Yue
Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA.
Int J Biomed Imaging. 2007;2007:74143. doi: 10.1155/2007/74143.
In recent years, there has been an increasing interest in studying the propagation of polarized light in biological cells and tissues. This paper presents a novel approach to cell or tissue imaging using a full Stokes imaging system with advanced polarization image analysis algorithms for improved diagnostics. The key component of the Stokes imaging system is the electrically tunable retarder, enabling high-speed operation of the system to acquire four intensity images sequentially. From the acquired intensity images, four Stokes vector images can be computed to obtain complete polarization information. Polarization image analysis algorithms are then developed to analyze Stokes polarization images for cell or tissue classification. Specifically, wavelet transforms are first applied to the Stokes components for initial feature analysis and extraction. Artificial neural networks (ANNs) are then used to extract diagnostic features for improved classification and prediction. In this study, phantom experiments have been conducted using a prototyped Stokes polarization imaging device. In particular, several types of phantoms, consisting of polystyrene latex spheres in various diameters, were prepared to simulate different conditions of epidermal layer of skin. The experimental results from phantom studies and a plant cell study show that the classification performance using Stokes images is significantly improved over that using the intensity image only.
近年来，对研究偏振光在生物细胞和组织中的传播的兴趣与日俱增。本文提出了一种新颖的细胞或组织成像方法，使用具有先进偏振图像分析算法的全斯托克斯成像系统来改进诊断。斯托克斯成像系统的关键组件是电可调延迟器，它使系统能够高速运行，依次获取四个强度图像。从获取的强度图像中，可以计算出四个斯托克斯矢量图像以获得完整的偏振信息。然后开发偏振图像分析算法来分析斯托克斯偏振图像以进行细胞或组织分类。具体而言，首先将小波变换应用于斯托克斯分量进行初始特征分析和提取。然后使用人工神经网络（ANN）提取诊断特征以改进分类和预测。在本研究中，使用原型斯托克斯偏振成像设备进行了模型实验。特别是，制备了几种由不同直径的聚苯乙烯乳胶球组成的模型，以模拟皮肤表皮层的不同情况。模型研究和植物细胞研究的实验结果表明，使用斯托克斯图像的分类性能比仅使用强度图像有显著提高。
