Graduate Theses & Dissertations

Advanced broadband CARS microscopy based on a supercontinuum-generating photonic crystal fiber
I have developed and improved a coherent anti-Stokes Raman scattering (CARS) microscope based on the spectral focusing (SF) technique. The CARS microscope uses an 800 nm oscillator and a photonic crystal fibre module to generate the supercontinuum Stokes. The photonic crystal fibre was originally designed to generate light beyond 945 nm which is useful for CARS microscopy in the CH/OH frequencies but essentially prevents access to the important fingerprint region at lower frequencies. With expert and nontraditional approaches to generating supercontinuum with sufficient power at wavelengths below 945 nm, I substantially extend the usefulness of the module for SF-CARS microscopy deep into the fingerprint region. Moreover, with the invention of a dynamic supercontinuum generation scheme we call "spectral surfing," I improve both the brightness of the CARS signal and extend the accessible CARS frequency range to frequencies as low as 350 cm$^{-1}$ and as high as 3500 cm$^{-1}$---all in a single scan-window. I demonstrate the capabilities of our broadband SF-CARS system through CARS and four-wave mixing hyperspectroscopy on samples such as astaxanthin, lily pollen and glass; liquid chemicals such as benzonitrile, nitrobenzene and dimethyl sulfoxide; and on pharmaceutical samples such as acetaminophen, ibuprofen, and cetirizine. Furthermore, In search of more useful Stokes supercontinuum sources, I compare the performance of two commercial photonic crystal fibre modules for use in SF-CARS applications, ultimately finding that one module provides better spectral characteristics for static supercontinuum use, while the other provides improved characteristics when spectral surfing is implemented. Author Keywords: coherent anti-Stokes Raman scattering, nonlinear microscopy, scanning microscopy, spectroscopy, supercontinuum generation, vibrational spectroscopy
"Multimodal Contrast" from the Multivariate Analysis of Hyperspectral CARS Images
The typical contrast mechanism employed in multimodal CARS microscopy involves the use of other nonlinear imaging modalities such as two-photon excitation fluorescence (TPEF) microscopy and second harmonic generation (SHG) microscopy to produce a molecule-specific pseudocolor image. In this work, I explore the use of unsupervised multivariate statistical analysis tools such as Principal Component Analysis (PCA) and Vertex Component Analysis (VCA) to provide better contrast using the hyperspectral CARS data alone. Using simulated CARS images, I investigate the effects of the quadratic dependence of CARS signal on concentration on the pixel clustering and classification and I find that a normalization step is necessary to improve pixel color assignment. Using an atherosclerotic rabbit aorta test image, I show that the VCA algorithm provides pseudocolor contrast that is comparable to multimodal imaging, thus showing that much of the information gleaned from a multimodal approach can be sufficiently extracted from the CARS hyperspectral stack itself. Author Keywords: Coherent Anti-Stokes Raman Scattering Microscopy, Hyperspectral Imaging, Multimodal Imaging, Multivariate Analysis, Principal Component Analysis, Vertex Component Analysis

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2011 - 2021
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Format: 2021/03/08

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