| Autor: |
Federico Vernuccio, Alejandro De la Cadena, Giulio Cerullo, Carlo Michele Valensise, Dario Polli |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
Advanced Chemical Microscopy for Life Science and Translational Medicine 2021. |
| DOI: |
10.1117/12.2578587 |
| Popis: |
We present innovative approaches to broadband coherent Raman scattering microscopy, both in the stimulated Raman scattering (SRS) and broadband coherent anti-Stokes Raman scattering (CARS) modalities. A convolutional neural network removes the unwanted non-resonant background from broadband CARS spectra. The deep-learning model processes experimental data in 100microseconds and correctly retrieves all the relevant vibrational peaks without any user intervention or independent background measurement. A multi-channel lock-in amplifier, in combination with in-line balanced detection and a broadband optical parametric oscillator, allows sensitive measurement of the SRS spectrum at 32 frequencies in parallel, with pixel dwell times as short as 40 microseconds. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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