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Proceedings Paper

1064 nm Raman microscopy using a multifocal excitation pattern
Author(s): Haojie Ji; Marcos Oliveira; Che-Wei Chang; James W. Chan
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Paper Abstract

Raman microscopy is well recognized as a nondestructive, label-free biomedical imaging method that provides abundant chemical information of the specimen. Excitation wavelengths in deep near-infrared (e.g., 1064 nm) are used in certain situations, such as when analyzing photosensitive/photolabile specimens to suppress the strong fluorescence and to avoid photodamage. However, the speed and quality of 1064 nm Raman imaging suffers from the low scattering efficiency at this long excitation wavelength and the high noise level of InGaAs detectors. In this study, we investigated a multifocal patterned approach for 1064 nm Raman imaging. A 2-D Hadamard-coded multifocal array generated with X-Y scanning galvomirrors is used to excite and collect multiple Raman spectra simultaneously. The individual spectrum at each focus is retrieved and reconstructed from the superimposed spectra of the multifocal patterns. We demonstrate that the multifocal approach improves both the signal-to-noise ratio (SNR) and the imaging speed of Raman microscopy. Compared to the traditional point scan, at optimal detector conditions, the multifocal approach can be two-times faster for achieving the same image quality and SNR, or provides spectra with three-times higher SNR while applying the same energy dose at the focus. Such improvements of imaging speed and SNR increase up to one or two orders of magnitude under higher noise conditions, such as higher readout rate and higher detector temperatures. The multifocal approach presents advantages for certain imaging situations, such as when heating related damage limits the excitation energy dose that can be applied to the sample.

Paper Details

Date Published: 20 February 2020
PDF: 6 pages
Proc. SPIE 11251, Label-free Biomedical Imaging and Sensing (LBIS) 2020, 1125104 (20 February 2020); doi: 10.1117/12.2546771
Show Author Affiliations
Haojie Ji, Univ. of California, Davis (United States)
Marcos Oliveira, Univ. of California, Davis (United States)
Che-Wei Chang, Univ. of California, Davis (United States)
James W. Chan, Univ. of California, Davis (United States)

Published in SPIE Proceedings Vol. 11251:
Label-free Biomedical Imaging and Sensing (LBIS) 2020
Natan T. Shaked; Oliver Hayden, Editor(s)

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