Restoration and spectral recovery of mid-infrared chemical images.
Fourier transform infrared (FTIR) microspectroscopy is a powerful technique for label-free chemical imaging that has supplied important chemical information about heterogeneous samples for many problems across a variety of disciplines. State-of-the-art synchrotron based infrared (IR) microspectrometers can yield high-resolution images, but are truly diffraction limited for only a small spectral range. Furthermore, a fundamental trade-off exists between the number of pixels, acquisition time and the signal-to-noise ratio, limiting the applicability of the technique. The recently commissioned infrared synchrotron beamline, infrared environmental imaging (IRENI), overcomes this trade off and delivers 4096-pixel diffraction limited IR images with high signal-to-noise ratio in under a minute. The spatial oversampling for all mid-IR wavelengths makes the IRENI data ideal for spatial image restoration techniques. Here, we measured and fitted wavelength-dependent point-spread-functions (PSFs) at IRENI for a 74× objective between the sample plane and detector. Noise-free wavelength-dependent theoretical PSFs are deconvoluted from images generated from narrow bandwidths (4 cm(-1)) over the entire mid-infrared range (4000-900 cm(-1)). The stack of restored images is used to reconstruct the spectra. Restored images of metallic test samples with features that are 2.5 μm and smaller are clearly improved in comparison to the raw data images for frequencies above 2000 cm(-1). Importantly, these spatial image restoration methods also work for samples with vibrational bands in the recorded mid-IR fingerprint region (900-1800 cm(-1)). Improved signal-to-noise spectra are reconstructed from the restored images as demonstrated for a mixture of spherical polystyrene beads in a polyurethane matrix. Finally, a freshly thawed retina tissue section is used to demonstrate the success of deconvolution achievable with a heterogeneous, irregularly shaped, biologically relevant sample with distinguishing spectroscopic features across the entire mid-IR spectral range.
Department of Physics, University of Wisconsin, Milwaukee, Wisconsin 53211, United States.
Eric C
EC
Mattson
Michael J
MJ
Nasse
Margaret
M
Rak
Kathleen M
KM
Gough
Carol J
CJ
Hirschmugl
D000818:Animals; D051379:Mice; D011108:Polymers / Q000737:chemistry; D012160:Retina / Q000166:cytology; D013055:Spectrophotometry, Infrared / Q000379:methods*; D013223:Statistics as Topic / Q000379:methods*
D011108:Polymers