## 3 Results and Discussion
### Discrimination of Different Human Skin Tissues Using Vectorial Retardance
#### 3.2.2 Qualitative Assessment by True-Color Vectorial Retardance Imaging  
To demonstrate the feasibility of the vectorial retardance imaging method, we use the above homemade high-fidelity MMIP system to detect numerous unstained skin sections, including normal, BE, and MM tissues. Figure 5 shows different images of the same normal skin tissue. Figure 5 is the H&E stained section microscopic intensity image, which can be used to roughly identify different structures with different colors. Typically, the stained samples are visualized to analyze the microstructural variations in the clinic. However, the staining depends on the mechanism of the chemical reaction between the dye and the biological components [20], which leads to the alteration of molecular structures [21; 22] and may result in the optical property changes of tissues (e.g., the birefringence of collagen fibers) [34]. Thus, imaging unstained samples is more appropriate. It has been concluded that the distribution and orientation of fibers can serve as important evidence for early diagnosis and disease management [34]. Unfortunately, the traditional microscopic intensity images of unstained samples are less sensitive to anisotropic fibers. As shown in Figure 5, the intensity image of the unstained section provides a rough shape of the microstructures but fails to clearly show the distribution and orientation of fibers, such as the region pointed by the red arrow. The Mueller matrix microscopic imaging, whose results are shown in Figure 5-h, is a label-free and quantitative method. The horizontal retardance (Figure 5) and 45-linear retardance (Figure 5) show abundant and well-ordered collagen fibers distributed linearly. The region pointed out by the red arrow in Figure 5 highlights the clear distribution of the fibers along 45\({}^{\circ}\). In Figure 5, the values are much smaller, which is due to rare helically distributed fibers. As mentioned, each of the three retardance components can highlight the distribution of fibers with different orientations, which together can provide a complete description of the retardance of anisotropic tissues. However, interpreting the three components simultaneously is complex and challenging for pathological analysis. In Figure 5, larger scalar retardance values are mapped in the region distributing abundant fibers with strong birefringences, such as regions pointed by the circle with red lines and the rectangle with white lines. However, due to the square root of the sum of squares algorithm, many fiber details are filtered out [69] although the distribution and density of most fibers are highlighted in Figure 5. In Figure 5, although the orientation of linear retardance highlights fibers with different linear fast axes, the contrast is influenced by the absence of fiber distribution. Conversely, the vectorial retardance (Figure 5) allows the observation of birefringent fibers with enhanced contrast and more fiber details by directly visualizing the distribution and orientation simultaneously. Additionally, it is worth mentioning that the upper right corner in Figure 5 shows darker, which indicates weaker birefringence and less fiber content. This is because the area is mainly composed of squamous cells [23]. To further analyze the vectorial retardance images, the areas marked by the rectangle with white lines in Figure 5 are enlarged as shown in Figure 6. Each of the retardance components (Figure 6a, Figure 6b, or Figure 6c) can demonstrate the distribution of fibers with a specific orientation (for example, the horizontal retardance for fibers with a horizontal fast axis). The scalar retardance (Figure 6d) shows the distribution of all fibers but lacks orientation information. Figure 6e highlights the orientation of the mainly linear fibers by pseudo-colors but is absent in the fiber distribution. Although scalar retardance (Figure 6d) and orientation of linear retardance (Figure 6e) highlight fibers with birefringence properties, the contrast is influenced by inherent limitations [69].