Invited Article: Comparison of hyperspectral coherent Raman scattering microscopies for biomedical applications

被引：11

作者：

Bocklitz, T. ^{[1
,2
,3
]}

Meyer, T. ^{[1
,2
,3
]}

Schmitt, M. ^{[1
,2
]}

Rimke, I. ^{[4
]}

Hoffmann, F. ^{[5
]}

von Eggeling, F. ^{[1
,2
,5
]}

Ernst, G. ^{[3
,5
]}

Guntinas-Lichius, O. ^{[5
]}

Popp, J. ^{[1
,2
,3
]}

机构：

[1] Friedrich Schiller Univ Jena, Inst Phys Chem, Helmholtzweg 4, D-07743 Jena, Germany

[2] Friedrich Schiller Univ Jena, Abbe Ctr Photon, Helmholtzweg 4, D-07743 Jena, Germany

[3] Leibniz Inst Photon Technol IPHT, Leibniz Hlth Technol, Albert Einstein Str 9, D-07745 Jena, Germany

[4] APE Angew Phys & Elekt GmbH, Plauener Str 163-165, D-13053 Berlin, Germany

[5] Jena Univ Hosp, Dept Otorhinolaryngol, Haus A,Klinikum 1, D-07747 Jena, Germany

来源：

APL PHOTONICS | 2018年 / 3卷 / 09期

关键词：

VISUALIZATION; IMAGES;

D O I：

10.1063/1.5030159

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

Raman scattering based imaging represents a very powerful optical tool for biomedical diagnostics. Different Raman signatures obtained by distinct tissue structures and disease induced changes provoke sophisticated analysis of the hyperspectral Raman datasets. While the analysis of linear Raman spectroscopic tissue data is quite established, the evaluation of hyperspectral nonlinear Raman data has not yet been evaluated in great detail. The two most common nonlinear Raman methods are CARS (coherent anti-Stokes Raman scattering) and SRS (stimulated Raman scattering) spectroscopy. Specifically the linear concentration dependence of SRS as compared to the quadratic dependence of CARS has fostered the application of SRS tissue imaging. Here, we applied spectral processing to hyperspectral SRS and CARS data for tissue characterization. We could demonstrate for the first time that similar cluster distributions can be obtained for multispectral CARS and SRS data but that clustering is based on different spectral features due to interference effects in CARS and the different concentration dependence of CARS and SRS. It is shown that a direct combination of CARS and SRS data does not improve the clustering results. (C) 2018 Author(s).

引用

页数：8