Fast compressive Raman micro-spectroscopy to image and classify microplastics from natural marine environment.

The fast and reliable detection of micron-sized plastic particles from the natural marine environment is an important topic that is mostly addressed using spontaneous Raman spectroscopy. Due to the long (>tens of ms) integration time required to record a viable Raman signal, measurements are limited to a single point per microplastic particle or require very long acquisition times (up to tens of hours). In this work, we develop, validate, and demonstrate a compressive Raman technology using binary spectral filters and single-pixel detection that can image and classify six types of marine microplastic particles over an area of 1 mm2 with a pixel dwell time down to 1.75 ms/pixel and a spatial resolution of 1 µm. This is x10-100 faster than reported in previous studies.

Fast Compressive Raman Imaging of Polymorph Molecules and Excipients in Pharmaceutical Tablets.

We implement a near-infrared (NIR) version of compressive Raman imaging that incorporates a digital micromirror device (DMD) and a single-pixel detector for fast chemometric analysis and microscopic imaging. The NIR compressive Raman system is successfully used to detect and image active pharmaceutical ingredients exhibiting polymorphism within compact pharmaceutical tablets. We report the chemical imaging of a mixture of two clopidogrel polymorphs and three excipients in solid tablets with a pixel dwell time of 2.5 ms (0.5 ms per species). These results open the road to fast pharmaceutical tablet quality control imaging using compressive Raman technology.

Line-scan compressive Raman imaging with spatiospectral encoding.

We report a line-scanning imaging modality of compressive Raman technology with a single-pixel detector. The spatial information along the illumination line is encoded onto one axis of a digital micromirror device, while spectral coding masks are applied along the orthogonal direction. We demonstrate imaging and classification of three different chemical species.

Spatial frequency modulated imaging in coherent anti-Stokes Raman microscopy.

For sparse samples or in the presence of ambient light, the signal-to-noise ratio (SNR) performance of single-point-scanning coherent anti-Stokes Raman scattering (CARS) images is not optimized. As an improvement, we propose replacing the conventional CARS focus-point illumination with a periodically structured focus line while continuing to collect the transmitted CARS intensity on a single detector. The object information along the illuminated line is obtained by numerically processing the CARS signal recorded for various periods of the structured focus line. We demonstrate experimentally the feasibility of this spatial frequency modulated imaging (SPIFI) in CARS (SPIFI-CARS) and SHG (SPIFI-SHG) and identify situations where its SNR is better than that of the single-point-scanning approach.

Compressive Raman imaging with spatial frequency modulated illumination.

We report a line scanning imaging modality of compressive Raman technology with spatial frequency modulated illumination using a single pixel detector. We demonstrate the imaging and classification of three different chemical species at line scan rates of 40 Hz.

Assessment of Compressive Raman versus Hyperspectral Raman for Microcalcification Chemical Imaging.

We experimentally implement a compressive Raman technology (CRT) that incorporates chemometric analysis directly into the spectrometer hardware by means of a digital micromirror device (DMD). The DMD is a programmable optical filter on which optimized binary filters are displayed. The latter are generated with an algorithm based on the Cramer-Rao lower bound. We compared the developed CRT microspectrometer with two conventional state-of-the-art Raman hyperspectral imaging systems on samples mimicking microcalcifications relevant for breast cancer diagnosis. The CRT limit of detection significantly improves, when compared to the CCD based system, and CRT ultimately allows 100× and 10× faster acquisition speeds than the CCD- and EMCCD-based systems, respectively.

Precision of proportion estimation with binary compressed Raman spectrum.

The precision of proportion estimation with binary filtering of a Raman spectrum mixture is analyzed when the number of binary filters is equal to the number of present species and when the measurements are corrupted with Poisson photon noise. It is shown that the Cramer-Rao bound provides a useful methodology to analyze the performance of such an approach, in particular when the binary filters are orthogonal. It is demonstrated that a simple linear mean square error estimation method is efficient (i.e., has a variance equal to the Cramer-Rao bound). Evolutions of the Cramer-Rao bound are analyzed when the measuring times are optimized or when the considered proportion for binary filter synthesis is not optimized. Two strategies for the appropriate choice of this considered proportion are also analyzed for the binary filter synthesis.

Programmable single-pixel-based broadband stimulated Raman scattering.

We report a simple add-on for broadband stimulated Raman scattering (SRS) microscopes to enable fast and programmable spectroscopy acquisition. It comprises a conventional dispersive spectrometer layout incorporating a fast digital micromirror device (DMD). The approach is validated by acquiring SRS spectra of standard chemicals. We demonstrate a DMD's advantage in broadband SRS by showing higher signal-to-noise ratio using a multiplexed Hadamard spectral basis and compressive sensing detection. Our results apply to a variety of frequency-domain pump-probe spectroscopy.