Open Access
Issue
J. Eur. Opt. Soc.-Rapid Publ.
Volume 17, Number 1, 2021
Article Number 10
Number of page(s) 13
DOI https://doi.org/10.1186/s41476-021-00155-w
Published online 16 June 2021
  1. Zada L, Leslie HA, Vethaak AD, Tinnevelt GH, Jansen JJ, de Boer JF, Ariese F, Fast microplastics identification with stimulated Raman scattering microscopy. J. Raman Spectrosc. (2018) 49, 71136–1144. https://doi.org/10.1002/jrs.5367 [NASA ADS] [CrossRef] [Google Scholar]
  2. Freudiger CW, Min W, Saar BG, Lu S, Holtom GR, He C, Tsai JC, Kang JX, Xie XS, Label-free biomedical imaging with high sensitivity by stimulated Raman scattering microscopy. Science. (2008) 322, 59091857–1860. https://doi.org/10.1126/science.1165758 [NASA ADS] [CrossRef] [Google Scholar]
  3. Cheng, J.-X., Xie, X.S.: Coherent Raman scattering microscopy. Boca Raton: CRC Press; (2013). https://doi.org/10.1201/b12907 [Google Scholar]
  4. Ozeki Y, Dake F, Kajiyama S, Fukui K, Itoh K, Analysis and experimental assessment of the sensitivity of stimulated Raman scattering microscopy. Opt. Express (2009) 17, 53651–3658. https://doi.org/10.1364/oe.17.003651 [NASA ADS] [CrossRef] [Google Scholar]
  5. Nandakumar, P., Kovalev, A., Volkmer, A.: Vibrational imaging based on stimulated Raman scattering microscopy. New J. Phys. 11(3), (2009). https://doi.org/10.1088/1367-2630/11/3/033026 [Google Scholar]
  6. Slipchenko MN, Oglesbee RA, Zhang D, Wu W, Cheng JX, Heterodyne detected nonlinear optical imaging in a lock-in free manner. J. Biophotonics (2012) 5, 10801–807. https://doi.org/10.1002/jbio.201200005 [CrossRef] [Google Scholar]
  7. Saar BG, Freudiger CW, Reichman J, Stanley CM, Holtom GR, Xie XS, Video-rate molecular imaging in vivo with stimulated Raman scattering. Science. (2010) 330, 60091368–1370. https://doi.org/10.1126/science.1197236 [Google Scholar]
  8. Liao CS, Wang P, Wang P, Li J, Lee HJ, Eakins G, Cheng JX, Optical microscopy: spectrometer-free vibrational imaging by retrieving stimulated Raman signal from highly scattered photons. Sci. Adv. (2015) 1, 91–9. https://doi.org/10.1126/sciadv.1500738 [CrossRef] [Google Scholar]
  9. Ferrara MA, Filograna A, Ranjan R, Corda D, Valente C, Sirleto L, Three-dimensional label-free imaging throughout adipocyte differentiation by stimulated Raman microscopy. PLoS One (2019) 14, 51–16. https://doi.org/10.1371/journal.pone.0216811 [Google Scholar]
  10. Dickerscheid D, Lavalaye J, Romijn L, Habraken J, Contrast-noise-ratio (CNR) analysis and optimisation of breast-specific gamma imaging (BSGI) acquisition protocols. EJNMMI Res. (2013) 3, 11–9. https://doi.org/10.1186/2191-219X-3-21 [CrossRef] [Google Scholar]
  11. Welvaert M, Rosseel Y, On the definition of signal-to-noise ratio and contrast-to-noise ratio for fMRI data. PLoS One (2013) 8, 11e77089. https://doi.org/10.1371/journal.pone.0077089 [Google Scholar]
  12. Timischl F, The contrast-to-noise ratio for image quality evaluation in scanning electron microscopy. Scanning. (2015) 37, 154–62. https://doi.org/10.1002/sca.21179 [CrossRef] [Google Scholar]
  13. Adabi, S., Rashedi, E., Clayton, A., Mohebbi-Kalkhoran, H., Chen, X.W., Conforto, S., Nasiriavanaki, M.: A learnable despeckling framework for optical coherence tomography images. J. Biomed. Opt. 23, (2018). https://doi.org/10.1117/1.jbo.23.1.016013 [Google Scholar]
  14. Eybposh MH, Turani Z, Mehregan D, Nasiriavanaki M, Cluster-based filtering framework for speckle reduction in OCT images. Biomed. Opt. Express (2018) 9, 126359–6373. https://doi.org/10.1364/BOE.9.006359 [CrossRef] [Google Scholar]
  15. Fu D, Lu FK, Zhang X, Freudiger C, Pernik DR, Holtom G, Xie XS, Quantitative chemical imaging with multiplex stimulated Raman scattering microscopy. J. Am. Chem. Soc. (2012) 134, 83623–3626. https://doi.org/10.1021/ja210081h [CrossRef] [Google Scholar]
  16. Liao CS, Slipchenko MN, Wang P, Li J, Lee SY, Oglesbee RA, Cheng JX, Microsecond scale vibrational spectroscopic imaging by multiplex stimulated Raman scattering microscopy. Light Sci. Appl. (2015) 4, 31–9. https://doi.org/10.1038/lsa.2015.38 [Google Scholar]
  17. Zurich Instruments AG. HF2LI: HF2 User Manual, Revision 21.02.0. Zurich (2014). https://docs.zhinst.com/pdf/ziHF2_UserManual.pdf. [Google Scholar]
  18. Audier X, Heuke S, Volz P, Rimke I, Rigneault H, Noise in stimulated Raman scattering measurement: from basics to practice. APL Photonics (2020) 5, 11–33. https://doi.org/10.1063/1.5129212 [Google Scholar]
  19. Moester, M.J.B., Ariese, F., De Boer, J.F.: Optimized signal-to-noise ratio with shot noise limited detection in stimulated Raman scattering microscopy. J. Eur. Opt. Soc. 10, (2015). https://doi.org/10.2971/jeos.2015.15022 [Google Scholar]
  20. Wang K, Liang R, Qiu P, Fluorescence signal generation optimization by optimal filling of the high numerical aperture objective lens for high-order deep-tissue multiphoton fluorescence microscopy. IEEE Photonics J. (2015) 7, 61–8. https://doi.org/10.1109/JPHOT.2015.2505145 [NASA ADS] [Google Scholar]
  21. Hess ST, Webb WW, Focal volume optics and experimental artifacts in confocal fluorescence correlation spectroscopy. Biophys. J. (2002) 83, 42300–2317. https://doi.org/10.1016/S0006-3495(02)73990-8 [NASA ADS] [CrossRef] [Google Scholar]
  22. Moester MJB, Zada L, Fokker B, Ariese F, de Boer JF, Stimulated Raman scattering microscopy with long wavelengths for improved imaging depth. J. Raman Spectrosc. (2019) 50, 91321–1328. https://doi.org/10.1002/jrs.5494 [NASA ADS] [CrossRef] [Google Scholar]
  23. Thomann D, Rines DR, Sorger PK, Danuser G, Automatic fluorescent tag detection in 3D with super-resolution: application to the analysis of chromosome movement. J. Microsc. (2002) 208, 149–64. https://doi.org/10.1046/j.1365-2818.2002.01066.x [CrossRef] [Google Scholar]
  24. Inoue, S., Oldenbourg, R.: Microscopes. In: Bass, M., Van Stryland, E.W., Williams, D.R., Wolfe, W.L. (eds.) Handbook of optics, vol. 2, 2nd edn, pp. 17.1–17.52. New York City: McGraw-Hill, Inc; (1995) [Google Scholar]
  25. Benninger RKP, Piston DW, Two-photon excitation microscopy for the study of living cells and tissues. Curr. Protoc. Cell Biol. (2013) 59, 11–24. https://doi.org/10.1002/0471143030.cb0411s59 [Google Scholar]
  26. Wang, X., Zhan, Y., Liang, J., Chen, X.: Simulation of the stimulated Raman scattering signal generation in scattering media excited by Bessel beams. In Label-free Biomedical Imaging and Sensing (LBIS) 2019 (eds. Shaked, N. T. & Hayden, O.) 27, (SPIE, 2019). https://doi.org/10.1117/12.2508494. [Google Scholar]
  27. Rigneault, H., Berto, P.: Tutorial: coherent Raman light matter interaction processes. APL Photonics. 3(9), (2018). https://doi.org/10.1063/1.5030335 [Google Scholar]
  28. Ishibashi T, Cai Y, Polarization properties in apertureless-type scanning near-field optical microscopy. Nanoscale Res. Lett. (2015) 10, 1375. https://doi.org/10.1186/s11671-015-1062-5 [Google Scholar]
  29. Samolis PD, Sander MY, Phase-sensitive lock-in detection for high-contrast mid-infrared photothermal imaging with sub-diffraction limited resolution. Opt. Express (2019) 27, 32643–2655. https://doi.org/10.1364/oe.27.002643 [CrossRef] [Google Scholar]
  30. Totachawattana A, Liu H, Mertiri A, Hong MK, Erramilli S, Sander MY, Vibrational mid-infrared photothermal spectroscopy using a fiber laser probe: asymptotic limit in signal-to-baseline contrast. Opt. Lett. (2016) 41, 1179–182. https://doi.org/10.1364/ol.41.000179 [CrossRef] [Google Scholar]
  31. Baddour N, Theory and analysis of frequency-domain photoacoustic tomography. J. Acoust. Soc. Am. (2008) 123, 52577–2590. https://doi.org/10.1121/1.2897132 [NASA ADS] [CrossRef] [Google Scholar]
  32. Leboulluec P, Liu H, Yuan B, A cost-efficient frequency-domain photoacoustic imaging system. Cit. Am. J. Phys. (2013) 81, 9712–717. https://doi.org/10.1119/1.4816242 [CrossRef] [Google Scholar]
  33. van Haasterecht L, Zada L, Schmidt RW, de Bakker E, Barbé E, Leslie HA, Vethaak AD, Gibbs S, de Boer JF, Niessen FB, van Zuijlen PPM, Groot ML, Ariese F, Label-free stimulated Raman scattering imaging reveals silicone breast implant material in tissue. J. Biophotonics (2020) 13, 5e201960197. https://doi.org/10.1002/jbio.201960197 [Google Scholar]

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