Laserlab-Europe Talk: Compressive Raman imaging: a computational framework for high-speed chemical microscopy

Title: Compressive Raman imaging: a computational framework for high-speed chemical microscopy
Speaker: Hilton B. de Aguiar (CNRS, Laboratoire Kastler Brossel and Ecole Normale Superieure)
Date: Wednesday, 20 November 2024, 4:00pm CET

Registration see below

Raman imaging is recognized as a powerful label-free approach to provide contrasts based on chemical selectivity. Nevertheless, Raman-based microspectroscopy still have drawbacks precluding high-speed chemical imaging. The main issue is the inherent high data throughput in microspectroscopy: fast spectral imaging is challenging for dynamic and large-scale imaging due to its data acquisition, processing and representation change (from vibrational resonances amplitudes to chemicals concentration) procedures.

These challenges can be overcome by exploiting the concept of compressive Raman imaging: by leveraging the sparsity [1] and redundancy [2] in Raman data sets, one can develop computational procedures to considerably simplify and speed up the spectral image acquisition. Exploiting such framework, we have recently reached speeds compatible with video-rate imaging [3] by detecting just a handful of photons.

In this presentation, I will introduce and discuss the different ways of performing compressive Raman, in particular focusing on challenges for bio-imaging, and also show more recent results applied to long-time imaging of electrochemical systems [4].

References
[1] Sturm et al, ACS Photon. 6, 1409 (2019); Scotte et al. Anal. Chem. 90, 7197 (2018).
[2] Soldevila et al, Optica 6, 341 (2019).
[3] Gentner et al, Opt. Lett. in print (2024).
[4] Pandya et al, Nat. Comm. 15, 8362 (2024).