KEYWORDS: Raman spectroscopy, Biological imaging, Cell death, Signal to noise ratio, Image quality, Spatial resolution, Singular value decomposition, Yield improvement, Super resolution, Spectral density
Raman imaging has become a vital tool for studying biological processes thanks to its label-free and non-invasive nature. However, photodamage has been a long-term concern in Raman imaging which requires large number of photons to produce enough contrast due to its inherent weak scattering efficiency. In this paper, we proposed to optimize the instrument slit-width and leverage deep learning approach to accelerate the Raman imaging, and thereby reduce the photodamage. Experiment results have shown that the collaborative effort yields Raman image with high SNR, SR and SpR, whose quality is comparable to the image obtained using narrow slits, small scan steps, and long integration times, while an 80-fold improved imaging speed allows the photodamage to be reduced greatly. Subsequently, we have been successfully employed it to observe the dynamic changes of cytochrome c in a single cell during the apoptotic before reaching the photodamage limit. It is a new endeavor in the study of cell dynamics and provides a reliable tool for more observation of other biochemical processes.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.