Malignant melanoma is considered the most serious type of skin cancer. In clinical practice, the conventional technique based on subjective visual examination has a high rate of misdiagnosis for malignant melanoma and benign nevus. Polarization imaging techniques have great potential in clinical diagnosis due to the advantages of improving sensitivity to functional structures, such as microfiber. In this paper, a set of human skin tissue sections, including 853 normal, 851 benign nevus, and 874 malignant melanoma, were analyzed and differentiated using a homemade high-fidelity Mueller matrix imaging polarimeter. The quantitative result using support vector machine algorithms confirmed that, while scalar retardance yields lower accuracy rates, vectorial retardance results in greater accuracy for both the training and testing sets. In particular, the cross-validation accuracy for the training set increased from 88.33% to 98.60%, and the prediction accuracy for the testing set increased from 87.92% to 96.19%. This tackles the limitation of the examination based on clinical experience and suggests that vectorial retardance can provide more accurate diagnostic evidence than scalar retardance. Unfortunately, it is inconvenient and time-consuming to read and analyze each component of the vectorial retardance simultaneously in the qualitative assessment. To address this clinical challenge, a color-encoded vectorial retardance imaging method was implemented. This method can provide superior tissue-specific contrast and more fiber details than scalar retardance. The anisotropic microfiber variation among different skin lesions, including the orientation and distribution, can be clearly highlighted. We believe that this work will not only enable early and rapid diagnosis of skin cancer but also provide a good observation and analysis of the state of cancer progression.

As a serious threat to women's lives and health, cervical cancer ranks second only to breast cancer in the incidence rate and mortality rate among female tumors in the world. Early diagnosis and treatment could be conducive to improving patients' survival activity index. Mueller matrix imaging polarimeter can detect the full polarization characteristics of a sample, and has shown an optimistic prospect in diagnosing various diseases. By analyzing the polarization parameters related to scattering and optical anisotropic properties of samples, detailed microstructure information can be obtained. In this paper, an in-house high-precision Mueller matrix imaging polarimeter with an objective lens NA of 0.40 was used to detect dewaxed, unstained, and unsealed cervical pathological sections, including 325 cases of CIN 1, CIN 2, CIN 3, and normal cervical tissues respectively. The Mueller matrix polar decomposition parameters, including depolarization, retardance, and diattenuation of different degrees of cervical tissues are derived. The relationship between the structure and polarization characteristics of different lesions was analyzed. Furthermore, by utilizing the receiver operating characteristic (ROC) curves, the optimal diagnostic threshold, specificity and sensitivity are calculated. Simultaneously, the diagnostic reliability of the MMIP with different polarization parameters among normal, CIN 1, CIN-2, and CIN-3 cervical tissue sections is demonstrated at about 82.8%-99.8%. This study proves the reliability and effectiveness of the self-developed MMIP in the detection of cervical tissue sections and is expected to become a powerful tool to assist doctors in pathological diagnosis.