Filters

2017 - 20192

More filters

2019 - 20202
Reset filters

Settings

Author: Popp, Jürgen × Author: Stiebing, Clara × End date: 2019 × Start date: 2014 × Subject: Raman spectroscopy ×

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Evaluation of shifted excitation Raman difference spectroscopy and comparison to computational background correction methods applied to biochemical Raman spectra
    (Basel : MDPI, 2017) Cordero, Eliana; Korinth, Florian; Stiebing, Clara; Krafft, Christoph; Schie, Iwan W.; Popp, Jürgen
    Raman spectroscopy provides label-free biochemical information from tissue samples without complicated sample preparation. The clinical capability of Raman spectroscopy has been demonstrated in a wide range of in vitro and in vivo applications. However, a challenge for in vivo applications is the simultaneous excitation of auto-fluorescence in the majority of tissues of interest, such as liver, bladder, brain, and others. Raman bands are then superimposed on a fluorescence background, which can be several orders of magnitude larger than the Raman signal. To eliminate the disturbing fluorescence background, several approaches are available. Among instrumentational methods shifted excitation Raman difference spectroscopy (SERDS) has been widely applied and studied. Similarly, computational techniques, for instance extended multiplicative scatter correction (EMSC), have also been employed to remove undesired background contributions. Here, we present a theoretical and experimental evaluation and comparison of fluorescence background removal approaches for Raman spectra based on SERDS and EMSC.
  • Thumbnail Image
    Item
    Application of High-Throughput Screening Raman Spectroscopy (HTS-RS) for Label-Free Identification and Molecular Characterization of Pollen
    (Basel : MDPI, 2019) Mondol, Abdullah S.; Patel, Milind D.; Rüger, Jan; Stiebing, Clara; Kleiber, Andreas; Henkel, Thomas; Popp, Jürgen; Schie, Iwan W.
    Pollen studies play a critical role in various fields of science. In the last couple of decades, replacement of manual identification of pollen by image-based methods using pollen morphological features was a great leap forward, but challenges for pollen with similar morphology remain, and additional approaches are required. Spectroscopy approaches for identification of pollen, such as Raman spectroscopy has potential benefits over traditional methods, due to the investigation of the intrinsic molecular composition of a sample. However, current Raman-based characterization of pollen is complex and time-consuming, resulting in low throughput and limiting the statistical significance of the acquired data. Previously demonstrated high-throughput screening Raman spectroscopy (HTS-RS) eliminates the complexity as well as human interaction by incorporation full automation of the data acquisition process. Here, we present a customization of HTS-RS for pollen identification, enabling sampling of a large number of pollen in comparison to other state-of-the-art Raman pollen investigations. We show that using Raman spectra we are able to provide a preliminary estimation of pollen types based on growth habits using hierarchical cluster analysis (HCA) as well as good taxonomy of 37 different Pollen using principal component analysis-support vector machine (PCA-SVM) with good accuracy even for the pollen specimens sharing similar morphological features. Our results suggest that HTS-RS platform meets the demands for automated pollen detection making it an alternative method for research concerning pollen.