Algorithm for in vivo detection of tissue type from multiple scattering light phase images

In vivo physiological assessments are typically done by either imaging techniques or by sensing changes in the attenuation coefficient. Using visible or near-infrared (NIR), imaging is mainly possible for thin tissues. On the other hand, clinical information can also be detected by examining changes in tissue optical properties. The most challenging aspect in sensing techniques is the spectral dependent scattering, which varies with the physiological state and tissue type. We have previously published our novel noninvasive nanophotonics technique for detecting tissue scattering based on reflectance measurements: The iterative multi-plane optical property extraction (IMOPE). The IMOPE reconstructs the reemitted light phase using an iterative algorithm and extracts the scattering properties based on a theoretical model. This paper presents the in vivo application of distinguishing between different mouse tissue areas. The reconstructed phase images reveal different areas in the inner thigh of a mouse, which are related to the muscle, bone, and skin. The IMOPE uses the reconstructed phases for sensing and detecting unseen components beneath the skin surface. This technique could be further applied to the diagnosis of various physiological states.