Fourier
transform infrared spectroscopy has emerged as a powerful
tool for tissue specimen investigation. Its nondestructive and label-free
character enables direct determination of biochemical composition
of samples. Furthermore, the introduction of polarization enriches
this technique by the possibility of molecular orientation study apart
from purely quantitative analysis. Most of the molecular orientation
studies focused on polymer samples with a well-defined molecular axis.
Here, a four-polarization approach for Herman’s in-plane orientation
function and azimuthal angle determination was applied to a human
tissue sample investigation for the first time. Attention was focused
on fibrous tissues rich in collagen because of their cylindrical shape
and established amide bond vibrations. Despite the fact that the tissue
specimen contains a variety of molecules, the presented results of
molecular ordering and orientation agree with the theoretical prediction
based on sample composition and vibration directions.
The recent emergence of High Definition (HD) FT-IR and Quantum Cascade Laser (QCL) Microscopes elevated the IR imaging field very close to clinical timescales. However, the speed of acquisition and data quality are still the critical factors in reaching the clinic. Denoising offers aide in both aspects if performed properly. However, there is a lack of a direct comparison of the efficiency of denoising techniques in IR imaging in general. To achieve such comparison within a rigorous framework and obtaining the critical information about signal loss, a simulated dataset strongly bound by experimental parameters was created. Using experimental structural and spectral information and experimental noise levels data as an input for the simulation, a direct comparison of spatial (Fourier transform, Mean Filter, Weighted Mean Filter, Gauss Filter, Median Filter, spatial Wavelets and Deep Neural Networks) and spectral (Savitzky-Golay, Fourier transform, Principal Component Analysis, Minimum Noise Fraction and spectral Wavelets) denoising schemes was enabled. All of these techniques were compared on the simulated dataset, taking into account SNR gain, signal distortion and sensitivity to tuning parameters as comparison metrics. Later, the best techniques were applied to experimental data for validation. The results presented here clearly show the benefit of using hyperspectral denoising schemes such as PCA and MNF which outperform other methods.
When a sample has an anisotropic structure, it is possible
to obtain
additional information controlling the polarization of incident light.
With their straightforward instrumentation approaches, infrared (IR)
and Raman spectroscopies are widely popular in this area. Single-band-based
determination of molecular in-plane orientation, typically used in
materials science, is here extended by the concurrent use of two vibration
bands, revealing the orientational ordering in three dimension. The
concurrent analysis was applied to IR spectromicroscopic data to obtain
orientation angles of a model polycaprolactone spherulite sample.
The applicability of this method spans from high-resolution, diffraction-limited
Fourier transform infrared (FT-IR) and Raman imaging to super-resolved
optical photothermal infrared (O-PTIR) imaging. Due to the nontomographic
experimental approach, no image distortion is visible and nanometer
scale orientation domains can be observed. Three-dimensional (3D)
bond orientation maps enable in-depth characterization and consequently
precise control of the sample’s physicochemical properties
and functions.
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