Friday 28 Sep 2018Compressive Raman microspectroscopy

Hilton B. da Aguiar - cole Normale Suprieure

Newman Red 12:30-13:30

aman imaging is recognized as a powerful label-free microscopy technique, providing high spatial resolution with superb molecular selectivity. Raman imaging exploits the intrinsic vibrational spectra of molecules as a fingerprint. However, such high chemical selectivity comes at a price of acquiring large data sets. In particular, the hyperspectrum of Raman-based microspectroscopies precludes high bandwidth (e.g. video-rate imaging) or large-scale microscopies, aspects that are extremely important for the promising applications of Raman microscopy in biology and biomedicine.

Following the compressive sensing spirit, various approaches were proposed to demonstrate compressive Raman microspectroscopy: obtain the same information as the traditional imaging method, however, by experimentally acquiring less data. Compressive Raman borrows concepts from signal processing methods (aka compressive sensing), exploiting the fact that both the vibrational spectrum and the “chemical components space” are sparse.

Based on this sparsity assumption, one design an experiment which will sample these spaces in a more efficient way, followed by computational reconstruction.

In this presentation, I will introduce the concepts and present different flavors for performing compressive Raman, both in the spontaneous and coherent versions. I will particularly focus on the challenges that precludes fast imaging of biological specimens. I will show how this blend of concepts enabled simple spectroscopic acquisition in Stimulated Raman Scattering, and also faster and higher sensitivity imaging than traditional approaches for spontaneous Raman microspectroscopy.

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