In the recent years, numerous adaptive optics techniques have emerged to address optical aberrations in fluorescence microscopy imaging. However, many existing methods involve complex hardware implementations or lengthy iterative algorithms that may induce photo-damage to the sample. Our study proposes an innovative approach centered around a novel detector array capable of potentially capturing the probed sample in a single acquisition. Our solution is gentle on the sample and applicable to any laser scanning microscope equipped with a detector array. We demonstrate that the multi-dimensional dataset obtained using the detector array inherently encodes information about optical aberrations. Finally, we propose a convolutional neural network approach to decode these optical aberrations in real-time and with high accuracy, establishing the foundation for a new class of adaptive optics laser-scanning microscopy methods.
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.