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Sparse sampling for fast hyperspectral coherent anti-Stokes Raman scattering imaging

Masia, Francesco, Borri, Paola and Langbein, Wolfgang Werner 2014. Sparse sampling for fast hyperspectral coherent anti-Stokes Raman scattering imaging. Optics Express 22 (4) , pp. 4021-4028. 10.1364/OE.22.004021

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Abstract

We demonstrate a method to increase the acquisition speed in coherent anti-Stokes Raman scattering (CARS) hyperspectral imaging while retaining the relevant spectral information. The method first determines the important spectral components of a sample from a hyperspectral image over a small number of spatial points but a large number of spectral points covering the accessible spectral range and sampling the instrument spectral resolution at the Nyquist limit. From these components we determine a small set of frequencies needed to retrieve the weights of the components with minimum error for a given measurement noise. Hyperspectral images with a large number of spatial points, for example covering a large spatial region, are then measured at this small set of frequencies, and a reconstruction algorithm is applied to generate the full spectral range and resolution. The resulting spectra are suited to retrieve from the CARS intensity the CARS susceptibility which is linear in the concentration, and apply unsupervised quantitative analysis methods such as FSC3 [1]. We demonstrate the method on CARS hyperspectral images of human osteosarcoma U2OS cell, with a reduction in the acquisition time by a factor of 25. This method is suited also for other coherent vibrational microscopy techniques such as stimulated Raman scattering, and in general for hyperspectral imaging techniques with sequential spectral acquisition.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Physics and Astronomy
Biosciences
Publisher: Optical Society of America
ISSN: 1094-4087
Funders: EPSRC, BBSRC, EU
Date of First Compliant Deposit: 18 February 2019
Date of Acceptance: 3 February 2014
Last Modified: 15 Sep 2019 22:43
URI: http://orca.cf.ac.uk/id/eprint/58719

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