Polarimetric-based pseudocoloration techniques for identification of brain tissue

Polarimetric techniques have widely demonstrated their potential in biophotonics due to its capability to obtain relevant information from biological samples in a noninvasive and nondestructive way. Different polarimetric observables, obtained from the Mueller matrix of a sample, are used to explore the potential of these techniques in pathology detection or different biological structures classification. The physical properties of a sample related to polarization can be divided in three main groups: retardance, dichroism and depolarization. In this work, we propose the study of the polarimetric observables related to these physical properties for the identification of different structures in a biological sample by means of different pseudo-coloration methods. In particular, we study pseudo-coloration functions based on the Gaussian and Cauchy probabilistic functions. These probabilistic functions allow us to compute the probability of a given part of a sample to belong to a particular class (i.e. healthy or pathological or different structures in the same sample) where, this probability depends on the polarimetric observables obtained from the studied sample. We present a study of the different observables and methods to find the best approach for brain tissue identification (identification of gray and white matter in ex-vivo cow brain) and, which may be of interest in multiple biomedical scenarios such as early pathology detection and diagnosis or enhanced visualization of different structures for clinical applications.