Random forest microplastic classification using spectral subsamples of FT-IR hyperspectral images.

In this work, a random decision forest model is built for fast identification of Fourier-transform infrared spectra of the eleven most common types of microplastics in the environment. The random decision forest input data is reduced to a combination of highly discriminative single wavenumbers selected using a machine learning classifier. This dimension reduction allows input from systems with individual wavenumber measurements, and decreases prediction time. The training and testing spectra are extracted from Fourier-transform infrared hyperspectral images of pure-type microplastic samples, automatizing the process with reference spectra and a fast background correction and identification algorithm. Random decision forest classification results are validated using procedurally generated ground truth. The classification accuracy achieved on said ground truths are not expected to carry over to environmental samples as those usually contain a broader variety of materials.

Biomedical applications of mid-infrared quantum cascade lasers - a review.

Mid-infrared spectroscopy has been applied to research in biology and medicine for more than 20 years and conceivable applications have been identified. More recently, these applications have been shown to benefit from the use of quantum cascade lasers due to their specific properties, namely high spectral power density, small beam parameter product, narrow emission spectrum and, if needed, tuning capabilities. This review provides an overview of the achievements and illustrates some applications which benefit from the key characteristics of quantum cascade laser-based mid-infrared spectroscopy using examples such as breath analysis, the investigation of serum, non-invasive glucose monitoring in bulk tissue and the combination of spectroscopy and microscopy of tissue thin sections for rapid histopathology.

On the role of interference in laser-based mid-infrared widefield microspectroscopy.

A laser's high degree of coherence leads to interferences, which-in the absence of precautions-can cause severe image distortions such as fringes and speckles and which thereby strongly hamper a meaningful interpretation of hyperspectral images in laser-based widefield microspectroscopy. While images and spectra of homogenous samples may already suffer from interferences, any structured object such as a tissue thin section will add to these distortions due to wavelength- and, in particular, sample-dependent phase shifts (structure sizes, absorption coefficients, refractive indices). This effect is devastating for the universal applicability of laser-based microspectroscopy especially in the mid-infrared (MIR), where cell sizes are of the same dimension as the wavelength of the illumination source. Here, we show that the impact of interferences is strongly mitigated by reducing the time-averaged spatiotemporal coherence properties of the illumination using a moving plus a stationary scatterer. In this case, the illumination path provides a pseudothermal radiation source and spatially resolved spectra can be obtained at the quality of the reference method, that is, Fourier-transform infrared microspectroscopy, without compromising spectral or spatial resolution.

Optical properties of porcine dermis in the mid-infrared absorption band of glucose.

The optical properties of skin in the mid-infrared range are not known, despite their importance for e.g. non-invasive glucose monitoring. In this paper, transmission, absorption, scattering, and reduced scattering coefficients are quantified using a custom-built goniometer based on a quantum cascade laser operated at the glucose absorption band at a wavelength of around 9.7 µm. The measurements show a strong dominance of absorption and moderate contributions from scattering. The scattered radiation is dominated by single scattering events in the forward direction (g = 0.967) within the range of the investigated dermis layer thicknesses of up to 50 µm, whereby the fraction of multiple scattering is expected to increase with the layer thickness.

Real-time mid-infrared imaging of living microorganisms.

The speed and efficiency of quantum cascade laser-based mid-infrared microspectroscopy are demonstrated using two different model organisms as examples. For the slowly moving Amoeba proteus, a quantum cascade laser is tuned over the wavelength range of 7.6 µm to 8.6 µm (wavenumbers 1320 cm(-1) and 1160 cm(-1) , respectively). The recording of a hyperspectral image takes 11.3 s whereby an average signal-to-noise ratio of 29 is achieved. The limits of time resolution are tested by imaging the fast moving Caenorhabditis elegans at a discrete wavenumber of 1265 cm(-1) . Mid-infrared imaging is performed with the 640 × 480 pixel video graphics array (VGA) standard and at a full-frame time resolution of 0.02 s (i.e. well above the most common frame rate standards). An average signal-to-noise ratio of 16 is obtained. To the best of our knowledge, these findings constitute the first mid-infrared imaging of living organisms at VGA standard and video frame rate.