基于偏振成像的乳腺癌病理切片检测方法

生物组织具有与其结构和功能相关的固有光学特性，偏振成像技术能够根据组织正常和恶性变化之间的微观结构差异，表现出不同的偏振特性，从而实现两者区分。本研究设计了一套采集组织背向散射光Mueller矩阵的自动成像系统，对两种常见的乳腺癌病理组织切片分别进行Mueller矩阵成像实验，并对所得到的Mueller矩阵图像数据采用Mueller矩阵分解方法，分别提取出样本Mueller矩阵中具有清晰物理意义的参数图像。实验结果表明，相应的Mueller矩阵分解参数图像可以区分癌变组织和非癌变组织。这为乳腺癌的快速病理诊断提供了一种新的思路。

Detection of Pathological Sections of Breast Cancer Based on Polarization Imaging

Biological tissue has its inherent optical properties related to its structure and function. Polarization imaging technology can show different polarization characteristics according to the microstructure difference between normal and malignant changes of tissues, so as to distinguish between the two.In this study, a set of automatic imaging system is designed to collect the Mueller matrix of tissue backscatter light. The Mueller matrix imaging experiments are carried out on two kinds of common breast cancer pathological tissue sections, and the Mueller matrix image data obtained by Mueller matrix decomposition method are used to extract the clear physical meaning parameter images in the Mueller matrix. The experimental results show that the corresponding Mueller matrix decomposition parameter image can distinguish cancerous tissue from non cancerous tissue. This provides a new way for the rapid pathological diagnosis of breast cancer.