Depth-Resolved Imaging in Turbid Media via Polarimetry

Accurately locating diseased tissue and determining its depth are essential for effective drug penetration and surgical treatments. This study focuses on determining tissue depth in turbid media using polar-imetry, specifically targeting fibrous tissues. We constructed a tissue phantom that can quantitatively regulate depth to simulate fibrosis at specific layers. By analyzing measurement results from the Mueller matrix across depth gradients, we established correlations between basic polarization parameters (PBPs) and depth using machine learning algorithms. This research innovatively combines degree of polari-zation (DOP)-sensitive PBPs with anisotropy-sensitive PBPs to create depth polarization feature pa-rameters (DSPFPs). These DSPFPs are more sensitive to depth in shallow layers while maintaining accuracy in deeper layers. Additionally, we achieved 2-D depth-resolved imaging on phantoms, con-firming the effectiveness and robustness of this approach. Overall, this study not only broadens the application of polarimetry but also introduces a method for depth extraction.