Enhancing biological tissue structures visualization through polarimetric parameters

Abstract

Polarimetrical imaging is a noninvasive optical technique of great interest in biophotonics since it has the capability of obtaining relevant information of biological samples, being useful, for instance, for the early detection of diseases or the classification of biological structures, both on animal and vegetal tissues. Different structures produce different outcomes when interacting with light due to their polarimetric properties such as depolarization, dichroism or retardance. An exhaustive polarimetric analysis of these characteristics can unveil the relation between the tissue inherent characteristics and its polarimetric response, enabling us to find the most appropriate polarimetric parameters to describe or study a sample. These polarimetric characteristics can be obtained through the experimental measurement of the Mueller matrix (M) of a sample, from which a range of different polarimetric observables, giving physical interpretation, can be deduced. By taking advantage of these parameters, we propose a study of the suitability of different groups of metrics for the contrast enhancement in biological tissues imaging, taking special attention on some depolarization metrics and some physical parameters such as the wavelength or the angle of incidence of the illumination light. The results obtained suggest the convenience of certain parameters which may be of interest in multiple biomedical scenarios such as pathology early detection or enhanced visualization of different structures for clinical applications.

Polarimetric-based pseudocoloration techniques for identification of brain tissue

“…In the literature we can find pseudo-colored approaches using different probability functions. [12][13][14] In this case, to construct the pseudo-colored images we have chosen the functions presented in sec.2.1: the Normal distribution based algorithm and the Cauchy probabilistic function based algorithm. Fig.…”

“…In addition, the study of the polarimetric observables can be extended for the implementation of pseudo-colored methods. [12][13][14] These methods take profit of polarimetric observables to construct improved images based on these characteristics, enhancing the visualization and allowing to the automatic detection of certain structures in biological samples. For instance, pathological zones in plants 13 or different structures in tissues.…”

“…For instance, pathological zones in plants 13 or different structures in tissues. 12,14,15 In this work we want to inspect the suitability of a set of polarimetric observables to identify different classes of tissues in a sample. To do that, after studying the polarimetric response of the samples, we implement different pseudo-colored functions based in the most suitable polarimetric observables to further enhance the visualization of biological structures.…”

Polarimetric Images of Biological Tissues Based on the Arrow Decomposition of Mueller Matrices

“…A number of these observables have also proved their suitability in terms of biological tissue imaging and characterization [14][15][16][17][18][19]. This is because most biological samples show spatially heterogeneous polarimetric responses depending on the particular tissues they are composed of.…”

Polarization-Based De-Scattering Imaging in Turbid Tissue-like Scattering Media

“…), the accuracy of diagnosis using traditional attenuation-based imaging methods is greatly reduced. However, polarization imaging methods are highly sensitive to environmental structures, and the influence of light scattering on polarization states has been found to be very useful in surface or subsurface structural imaging as well as deep tissue transmission imaging [8][9][10]. Therefore, the combination of polarization imaging with traditional approaches will make biomedical diagnostic imaging more convenient and clearer.…”