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作 者:魏寒月 周逸夫 马菲雅 杨瑞 梁健 任立勇 WEI Hanyue;ZHOU Yifu;MA Feiya;YANG Rui;LIANG Jian;REN Liyong(School of Physics and Information Technology,Shaanxi Normal University,Xi'an 710119,Shaanxi,China;Xi'an Key Laboratory of Optical Information Manipulation and Augmentation(OMA),Xi'an 710119,Shaanxi,China;Robust(Xixian New Area)Opto-Electro Technologies Co.,Ltd,Xi'an 712000,Shaanxi,China)
机构地区:[1]陕西师范大学物理学与信息技术学院,陕西西安710119 [2]西安市光信息调控与增强技术重点实验室,陕西西安710119 [3]西咸新区诺博思特光电技术有限公司,陕西西安712000
出 处:《陕西师范大学学报(自然科学版)》2024年第6期48-56,共9页Journal of Shaanxi Normal University:Natural Science Edition
基 金:陕西省技术创新引导专项秦创原“科学家+工程师”队伍建设项目(2024QCY-KXJ-179);陕西省重点研发计划关键核心技术攻关项目(2024QY2-GJHX-45)。
摘 要:为实现对组织微阵列无损且迅速地鉴别,利用穆勒矩阵的偏振成像原理,构建了全自动穆勒矩阵显微成像系统。通过集成自动控制的偏振光学组件及成像设备,该系统能够进行自动成像。对收集的偏振图像数据,采用穆勒矩阵极分解与穆勒矩阵变换算法进行处理,以提取描述样本的关键偏振特征参数。结果发现:在区分宫颈癌组织样本与正常宫颈组织样本的实验中,等效波片快轴方位角θ和线相位延迟δ是有效的偏振参数;利用统计分析、灰度共生矩阵分析和Tamura图像处理方法对偏振参数图像进行处理,可以获得诊断宫颈癌的明确指征。全自动穆勒矩阵显微成像系统通过整合多个样本,无需频繁更换切片,且不需要切换到高倍物镜,从而达到对癌症的快速诊断。In order to achieve non-destructive and rapid inspection of tissue microarrays,a fully automatic Mueller matrix microscopic imaging system was constructed by using the polarization imaging principle of the Mueller matrix.By integrating polarization optical components and imaging equipment with automatic control,this system can perform automatic imaging.The collected polarized image data is processed by using the Mueller matrix polar decomposition and Mueller matrix transformation algorithms to extract the key polarization characteristic parameters describing the sample.The results showed that in the experiment of distinguishing cervical cancer tissue samples from normal cervical tissue samples,the equivalent waveplate fast-axis azimuthθand linear phase retardanceδare effective polarization parameters.By using statistical analysis,gray level co-occurrence matrix analysis and Tamura image processing methods to process the polarization parameter images,clear indications for diagnosing cervical cancer can be obtained.The fully automatic Mueller matrix microscopic imaging system can achieve rapid diagnosis of cancer by integrating multiple samples without frequently changing slices or switching to a high power objective.
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