Tissue classification interest is growing due to their numerous applications in the biomedical framework. This increasing interest leads to the rise of alternative techniques in order to enhance the classification accuracy. Polarimetric methods, and in particular, the study of depolarization properties of samples, appear to be an alternative and complementary technique that helps to discriminate between different organic tissues. In fact, depolarization is directly related with the scattering processes produced in biological tissues, providing different responses when studied in different fibre based structures. In the current state of art, there exists different metrics devised to study depolarizing properties of samples and it is not clear which method is the most suitable for tissue classification. By using some of those polarimetric metrics, a compendium of depolarizing spaces can be constructed, composed of three observables each. Such depolarizing spaces stand out over the other existing polarimetric indicators as they allow synthetizing the depolarization content of samples, to provide further analysis of depolarizers. In this work, we compare the effectivity of different depolarizing spaces in order to determine the best space for tissue classification. This is done by using a collection of chicken thigh tissues. In particular, we have measured the Mueller matrix of 120 samples spread around three chicken thigh tissues: tendon, muscle and myotendinous junction. Different tissues have been imaged at different wavelengths (470 nm, 530 nm and 625 nm) to obtain more information and to amplifying the classification sensitivity with this extra channel (wavelength). Finally, we conclude the work by showing the depolarization space providing the best results in terms of tissue classification.
This paper is devoted to investigating the application of different dynamic light structures generated by a self-calibrated Liquid Crystal on Silicon (LCoS) display for microparticle manipulation. Two major studies based on implementing different DOEs, to thoroughly characterize the LCoS display and to achieve optical-inspired particle manipulation, are proposed, respectively. On the one hand, we dynamically introduced two diffractive lens based patterns (the Billet-lens configuration and the micro-lens array pattern) on the LCoS display, from which the self-calibration of the studied device is implemented. In this case, both the phase-voltage relation and the surface profile were determined and optimized to the optimal performance for microparticle manipulation. On the other hand, we performed the optical manipulation of microparticles by addressing configurable three-dimensional light structures obtained from different phase driven split-lens configurations initiated by the same but optimized LCoS display. Experimental results demonstrated that, by addressing certain phase distributions on the LCoS display, the microparticle can be trapped in the light cones and manipulated by providing certain continuous split-lens configurations.
Recently, a set of polarimetric indicators, the Indices of Polarimetric Purity (IPPs), were described in the literature. These indicators allow synthesize depolarization content of samples, and provide further analysis of depolarizers than other existing polarimetric indicators. We demonstrate the potential of the IPPs as a criterion to characterize and classify depolarizing samples. In particular, the method is firstly analyzed through a series of basic polarization experiments, and we prove how differences in the depolarizing capability of samples, concealed from the commonly used depolarization index PΔ, are identified with the IPPs.
In the second part of this work, the method is experimentally highlighted by studying a rabbit leg ex-vivo sample. The obtained images of the ex-vivo sample illustrate how IPPs provide a significant enhancement in the image contrast of some biological tissues and, in some cases, present new information hidden in the usual polarimetric channels. Moreover, new physical interpretation of the sample can be derived from the IPPs which allow us to synthesize the depolarization behavior.
Finally, we also propose a pseudo-colored encoding of the IPPs information that provides an improved visualization of the samples. This last technique opens the possibility to highlight a specific tissue structure by properly adjusting the pseudo-colored formula.
We highlight the interest of using the Indices of Polarimetric Purity (IPPs) for the biological tissue inspection. These are three polarimetric metrics focused on the study of the depolarizing behaviour of the sample. The IPPs have been recently proposed in the literature and provide different and synthetized information than the commonly used depolarizing indices, as depolarization index (PΔ) or depolarization power (Δ). Compared with the standard polarimetric images of biological samples, IPPs enhance the contrast between different tissues of the sample and show differences between similar tissues which are not observed using the other standard techniques. Moreover, they present further physical information related to the depolarization mechanisms inherent to different tissues. In addition, the algorithm does not require advanced calculations (as in the case of polar decompositions), being the indices of polarimetric purity fast and easy to implement. We also propose a pseudo-coloured image method which encodes the sample information as a function of the different indices weights. These images allow us to customize the visualization of samples and to highlight certain of their constitutive structures. The interest and potential of the IPP approach are experimentally illustrated throughout the manuscript by comparing polarimetric images of different ex-vivo samples obtained with standard polarimetric methods with those obtained from the IPPs analysis. Enhanced contrast and retrieval of new information are experimentally obtained from the different IPP based images.
We present mathematical formulas generalizing polarization gating (PG) techniques. PG refers to a collection of imaging methods based on the combination of different controlled polarization channels. In particular, we show how using the measured Mueller matrix (MM) of a sample, a widespread number of PG configurations can be evaluated just from analytical expressions based on the MM coefficients. We also show the interest of controlling the helicity of the states of polarization used for PG-based metrology, as this parameter has an impact in the image contrast of samples. In addition, we highlight the interest of combining PG techniques with tools of data analysis related to the MM formalism, such as the well-known MM decompositions. The method discussed in this work is illustrated with the results of polarimetric measurements done on artificial phantoms and real ex-vivo tissues.