DescriptionOptical methods can provide non-contact imaging of blood, fat, water, and collagen distributions within tissue and visualization of these components can be important for clinical applications, basic science studies, and in research and development in the healthcare industry. To achieve accurate quantification, it is important to account for the 3D shape of the tissue being imaged, but conventional cameras cannot measure height or depth variations within a field of view. This project integrates a 3D imaging method called Phase Shifting Profilometry (PSP), with a method for quantifying tissue component concentrations called Spatial Frequency Domain Imaging (SFDI). PSP and SFDI were conveniently implemented through a single hardware setup that illuminated objects with structured light patterns and imaged the diffusely reflected light. Each step of the 3D phase profile extraction was defined and tested qualitatively. Then, various phase-to-height calibration relationships and methods were explored with reconstructions compared quantitatively with the actual measured heights of test objects. The accuracy of different 3D reconstruction algorithms was evaluated using calibrated phantoms, objects of various surface shapes and heights, and in vivo 3D imaging was demonstrated of a human subject’s face and hand. The process for extracting the 3D profile with height information was demonstrated to have 0.4 mm accuracy for flat planes and within 1 mm accuracy for topographically complex surfaces (such as in vivo hand and face profiles). Using the PSP data, the SFDI data was corrected to account for the 3D shape and depth of the tissue, allowing for the optical properties to be estimated with higher accuracy. Together, SFDI and PSP provide a powerful method for non-contact quantification of biological components that are important for monitoring tissue health, such as early diagnosis of wound complications,
and testing the effects of various products on tissue components.