A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
High-Speed Hyperspectral Imaging for Near Infrared Fluorescence and Environmental Monitoring
Tekijät: Stegemann, Jan; Groeniger, Franziska; Neutsch, Krisztian; Li, Han; Flavel, Benjamin Scott; Metternich, Justus Tom; Erpenbeck, Luise; Petersen, Poul Bering; Hedde, Per Niklas; Kruss, Sebastian
Kustantaja: WILEY
Kustannuspaikka: HOBOKEN
Julkaisuvuosi: 2025
Journal: Advanced Science
Tietokannassa oleva lehden nimi: ADVANCED SCIENCE
Lehden akronyymi: ADV SCI
Artikkelin numero: 2415238
Sivujen määrä: 12
eISSN: 2198-3844
DOI: https://doi.org/10.1002/advs.202415238
Verkko-osoite: https://doi.org/10.1002/advs.202415238
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/491393055
Hyperspectral imaging captures both spectral and spatial information from a sample but is intrinsically slow. The near infrared (NIR, > 800 nm) is advantageous for imaging applications because it falls into the tissue transparency window and also contains vibrational overtone and combination modes useful for molecular fingerprinting. Here, fast hyperspectral NIR imaging is demonstrated using a spectral phasor transformation (HyperNIR). A liquid crystal variable retarder (LCVR) is used for tunable, wavelength-dependent sine- and cosine-filtering that transforms optical signals into a 2D spectral (phasor) space. Spectral information is thus obtained with just three images. The LCVR can be adjusted to cover a spectral range from 900 to 1600 nm in windows tunable from 50 to 700 nm, which enables distinguishing NIR fluorophores with emission peaks less than 5 nm apart. Furthermore, label-free hyperspectral NIR reflectance imaging is demonstrated to identify plastic polymers and monitor in vivo plant health. The approach uses the full camera resolution and reaches hyperspectral frame rates of 0.2 s(-1), limited only by the switching rate of the LCVR. HyperNIR facilitates straightforward hyperspectral imaging for applications in biomedicine and environmental monitoring.
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This work was supported by the Fraunhofer Internal Programs under Grant No. Attract 038-610097 and funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy—EXC 2033—390677874—RESOLV. Additionally, this work was supported by the “Center for Solvation Science ZEMOS”, which was funded by the German Federal Ministry of Education and Research (BMBF) and the Ministry of Culture and Research of North Rhine-Westphalia. Further funding was provided by the VW Foundation.
Open access funding enabled and organized by Projekt DEAL.
