Light is an electromagnetic wave that can exist in various polarization states, including linear, circular and elliptical, and they exist in different forms of oscillating electric field electromagnetic wave components.
The polarization state of light is a very important property in optics-related applications, because the interaction of light with matter depends on the incident polarization state. For example, optical absorption experiments with linearly or circularly polarized light on molecular systems yield different results.
For molecules, when recorded with line polarized light, both enantiomers have the same absorption spectrum; however, with circularly polarized light, the two behave differently because the enantiomers preferentially absorb the monochiral nature of circularly polarized light. By this principle, the circular dichroism of the sample can be examined.
In biomedical imaging experiments, signals outside the target region, such as scattered signals near tissues, are often suppressed by polarization control. Some degree of depolarization is usually induced in the scattered light, so the polarizer can be considered as a filter to reduce unwanted scattering for the purpose of improving the signal-to-noise ratio of the image.
Polarization optics
The key to polarization control is the use of polarizing optical devices. There are several optical components used for optical control, including optically active crystals or dichroic materials used to make polarizers. Waveplates mounted on a rotating mount are often used when the polarization state needs to be changed in an experiment.
The waveplate will rotate the polarization of the incident light by introducing a phase delay between the polarization components. Waveplates are usually made of birefringent materials. The most common delay specification is λ/4, which produces a circular or elliptical polarization state and vice versa depending on the incident polarization angle of the incident polarized light, or λ/2, which is used for the rotation of the polarization axis of linearly polarized light. Waveplates are also capable of implementing another method of polarization control with a range of different phase variations.
Especially in microscopy and imaging applications, where polarization control is often used for scatter suppression, polarization information can also be used to extract additional information about the sample.
Polarization measurement techniques
There are several different experimental protocols that can be used to extract polarization information in imaging experiments. Scatter suppression methods are typically used for large tissue samples, while for thin tissue samples, polarization information can be used to distinguish image features of different diseases, for example, extremely similar Crohn’s disease and tuberculosis image features can be distinguished. Biomedical polarization imaging can be used for the diagnosis of many types of cancer, as well as for quantifying the stage of fibrosis in tissue samples.
The polarization of light can be viewed as a vector property, and the systems with which it interacts can also be viewed as vector information that can be used to describe the interactions between the systems. This requires the use of a range of formalisms that in turn can help predict features in the polarization data or interpret them.
Depending on whether the biological system in question undergoes a rapid exchange process over a short period of time, or whether time-averaged images are an acceptable description, or whether single excitation or time-series polarization measurements can be used. While some methods may recover the full polarization information, simpler and more direct experiments can recover some of this information.
While rotational polarizers are a cost-effective method for making many of these measurements, more advanced technologies, such as ferroelectric liquid crystals or spatial light modulators, are now available that also provide methods for rapid signal modulation, which can reduce the time to make important measurements in clinical applications.
Reflections
Machine learning techniques allow for automated image analysis and diagnosis of potential diseases, which has promising applications in biomedical and clinical imaging. Applying automatic image recognition to optical measurement devices can reduce the number of steps required to perform biopsies or sample analysis in the laboratory, which will provide more timely and more information for clinical decision making.
When commissioning imaging instruments, there is often a trade-off between spatial resolution and scan time; however, using deep learning and polarization measurement techniques will result in higher effective imaging resolution and improved quality of polarization measurement data, while also suppressing errors caused by artifacts in the experiment.
As optical technology continues to evolve, these can be incorporated into the feedback loop as part of the data acquisition process to reduce measurement time. Examples include the development of high-quality adaptive optics systems for full polarization control that have already been applied.
